From 3e9eedd3e325863d0b0b23133cef2e7ed7705bc4 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:15:18 +0900 Subject: [PATCH 01/34] test: Remove unused test codes --- tests/test_face_tagger.py | 4 ---- 1 file changed, 4 deletions(-) diff --git a/tests/test_face_tagger.py b/tests/test_face_tagger.py index 5833efc..8b13789 100644 --- a/tests/test_face_tagger.py +++ b/tests/test_face_tagger.py @@ -1,5 +1 @@ -from src.face_tagger.face_tagger import face_tagger - -def test_face_tagger(): - assert face_tagger() == "Hello Face Tagger" From ca7cb761756a045f1c0ce0bb9939b6063bf4f76f Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:18:33 +0900 Subject: [PATCH 02/34] feature: Add ImageObject class with a unique identifier and actual image data for distinction --- src/face_tagger/models/image_object.py | 4 ++++ 1 file changed, 4 insertions(+) create mode 100644 src/face_tagger/models/image_object.py diff --git a/src/face_tagger/models/image_object.py b/src/face_tagger/models/image_object.py new file mode 100644 index 0000000..41170d2 --- /dev/null +++ b/src/face_tagger/models/image_object.py @@ -0,0 +1,4 @@ +class ImageObject: + def __init__(self, image_id, image_data): + self.image_id = image_id + self.image_data = image_data From a7571bc4fb070d83404e26fdfe1fe8281565422a Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:18:53 +0900 Subject: [PATCH 03/34] feature: Add Detector class to detect faces from the provided image --- src/face_tagger/detector.py | 34 ++++++++++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 src/face_tagger/detector.py diff --git a/src/face_tagger/detector.py b/src/face_tagger/detector.py new file mode 100644 index 0000000..15d584f --- /dev/null +++ b/src/face_tagger/detector.py @@ -0,0 +1,34 @@ +from mtcnn import MTCNN + + +class Detector: + """ + Class for face detection. + """ + + def __init__(self): + """ + Constructor of Detector class. + """ + + self.face_detector = MTCNN() + + def detect_face_and_crop(self, image): + """ + Detects faces in an image and returns cropped face images. + + :param image: Image to detect faces. + :return: Cropped face images. + """ + + # Face detection using MTCNN. + faces = self.face_detector.detect_faces(image) + + # Crop face areas in the image. + cropped_faces = [] + for face in faces: + x, y, width, height = face['box'] + cropped_face = image[y:y + height, x:x + width] + cropped_faces.append(cropped_face) + + return cropped_faces From 0b3f7d6f419571967a5b54577532edbff206f3c8 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:19:17 +0900 Subject: [PATCH 04/34] feature: Add Embedder class to embed given image --- src/face_tagger/embedder.py | 44 +++++++++++++++++++++++++++++++++++++ 1 file changed, 44 insertions(+) create mode 100644 src/face_tagger/embedder.py diff --git a/src/face_tagger/embedder.py b/src/face_tagger/embedder.py new file mode 100644 index 0000000..5ef240b --- /dev/null +++ b/src/face_tagger/embedder.py @@ -0,0 +1,44 @@ +import cv2 +import torch +import torchvision.transforms as transforms +from PIL import Image +from facenet_pytorch import InceptionResnetV1 + + +class Embedder: + """ + Class for face embedding. + """ + + def __init__(self, use_gpu=False): + """ + Constructor of Embedder class. + + :param use_gpu: Use GPU or not. + """ + + self.device = torch.device('cuda' if use_gpu and torch.cuda.is_available() else 'cpu') + self.resnet = InceptionResnetV1(pretrained='vggface2').eval().to(self.device) + self.transform = transforms.ToTensor() + + def compute_embeddings(self, face_image): + """ + Compute embeddings of an image. + + :param face_image: An image to compute embeddings. + :return: Embeddings of an image. + """ + + # Resize the image to 160x160. + face_image = cv2.resize(face_image, (160, 160)) + + # Convert the image to RGB. + face_image = Image.fromarray(cv2.cvtColor(face_image, cv2.COLOR_BGR2RGB)) + + # Convert the image to tensor and add a batch dimension. + img_tensor = self.transform(face_image).unsqueeze(0).to(self.device) + + # Compute embeddings. + img_embedding = self.resnet(img_tensor) + + return img_embedding.cpu() From 03607589239be620b8bfef2e2516fdc81edda879 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:19:32 +0900 Subject: [PATCH 05/34] feature: Add Classifier class to grouping similar embeddings --- src/face_tagger/classifier.py | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) create mode 100644 src/face_tagger/classifier.py diff --git a/src/face_tagger/classifier.py b/src/face_tagger/classifier.py new file mode 100644 index 0000000..459369b --- /dev/null +++ b/src/face_tagger/classifier.py @@ -0,0 +1,28 @@ +import hdbscan +import torch + + +class Classifier: + """ + Class for face classification. + """ + def __init__(self): + """ + Constructor of Classifier class. + """ + + pass + + def classify_faces(self, face_embeddings): + """ + Cluster embeddings using HDBSCAN. + + :param face_embeddings: Embeddings to cluster. + :return: Cluster labels. + """ + + # Cluster embeddings using HDBSCAN. + embeddings_np = torch.stack(face_embeddings).view(len(face_embeddings), -1).detach().numpy() + hdbscan_cluster = hdbscan.HDBSCAN(min_cluster_size=2).fit(embeddings_np) + + return hdbscan_cluster.labels_ From ec5e1aa0733cab10e11ac6cbfb8af14529faf2f3 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:21:23 +0900 Subject: [PATCH 06/34] feature: Add FaceTagger class, the core component of the Face-Tagger library --- src/face_tagger/face_tagger.py | 88 +++++++++++++++++++++++++++++++++- 1 file changed, 86 insertions(+), 2 deletions(-) diff --git a/src/face_tagger/face_tagger.py b/src/face_tagger/face_tagger.py index f9a7662..596d6fb 100644 --- a/src/face_tagger/face_tagger.py +++ b/src/face_tagger/face_tagger.py @@ -1,2 +1,86 @@ -def face_tagger(): - return "Hello Face Tagger" +import cv2 + +from src.face_tagger.classifier import Classifier +from src.face_tagger.detector import Detector +from src.face_tagger.embedder import Embedder + + +class FaceTagger: + """ + Main class of the face tagger module. + """ + + def __init__(self, use_gpu=False, image_resize_factor=1.0): + """ + Constructor of FaceTagger class. + + :param use_gpu: Use GPU or not. + :param image_resize_factor: Resize factor of images. + """ + + self.detector = Detector() + self.embedder = Embedder(use_gpu) + self.classifier = Classifier() + self.image_resize_factor = image_resize_factor + + def classify_images_by_person(self, image_objects): + """ + Classifies images based on the person in the image. + + :param image_objects: Images to classify. + :return: Classified images. + """ + + face_embeddings = [] + processed_image_ids = [] + face_counts_per_image = {} + + classified_images = {"unclassified_images": []} + + # Embedding faces in each image. + for image_object in image_objects: + if self.image_resize_factor != 1.0: + image = cv2.resize(image_object.image_data, ( + int(image_object.image_data.shape[1] * self.image_resize_factor), + int(image_object.image_data.shape[0] * self.image_resize_factor))) + else: + image = image_object.image_data + + if image is not None: + cropped_faces = self.detector.detect_face_and_crop(image) + + if len(cropped_faces) == 0: + # If there is no face in the image, add the image to the list of unclassified images. + classified_images["unclassified_images"].append(image_object.image_id) + continue + + face_counts_per_image[image_object.image_id] = len(cropped_faces) + + # Compute embeddings of cropped faces. + for cropped_face in cropped_faces: + face_embedding = self.embedder.compute_embeddings(cropped_face) + face_embeddings.append(face_embedding) + processed_image_ids.append(image_object.image_id) + + # Classifying embedded faces. + groups = self.classifier.classify_faces(face_embeddings) + + # Grouping images by person. + for group, image_id in zip(groups, processed_image_ids): + if group != -1: + group_key = f"group_{group + 1}" + + if group_key not in classified_images: + # If the group is not in the dictionary, add the group. + classified_images[group_key] = {"main": None, "others": []} + + if face_counts_per_image[image_id] == 1: + # If there is only one face in the image, the face is the main face. + classified_images[group_key]["main"] = image_id + continue + + if image_id not in classified_images[group_key]["others"]: + # If the image is not in the list of other images, add the image. + classified_images[group_key]["others"].append(image_id) + + return classified_images From abb5ea126a2e4a20057d23d307fb2103d56f46c9 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:21:40 +0900 Subject: [PATCH 07/34] feature: Add __init__.py for models package --- src/face_tagger/models/__init__.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 src/face_tagger/models/__init__.py diff --git a/src/face_tagger/models/__init__.py b/src/face_tagger/models/__init__.py new file mode 100644 index 0000000..e69de29 From 2ac2a635a4150d7d94f4426b131fb3e799878177 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:22:28 +0900 Subject: [PATCH 08/34] chore: Import FaceTagger module int root of __init__.py --- src/face_tagger/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/src/face_tagger/__init__.py b/src/face_tagger/__init__.py index e69de29..e12a454 100644 --- a/src/face_tagger/__init__.py +++ b/src/face_tagger/__init__.py @@ -0,0 +1 @@ +from .face_tagger import FaceTagger From f2fa5e04bb3d4411e8661b9d6a615f599fe250f0 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 01:23:12 +0900 Subject: [PATCH 09/34] chore: Update requirements.txt with necessary library information --- requirements.txt | Bin 6 -> 6278 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/requirements.txt b/requirements.txt index 55b033e901cdda93a26ac64b418f260224260a39..3c24e14f0d819b8850be5ce104604ccac1189a00 100644 GIT binary patch literal 6278 zcmb7|TW=#p5QY00iT}VKnC#lwOF%*b@qmO_u~K;9DYD0xc-Ipf+qsw@51g;gRC=6* zm5}9JrmL$?Rh_D?o`3$Hlxf+QL)n!{Y4!U`|E;H}Z{$8I^IV-RA9hI-k zSCU<6KX}=(NyV!G%yDr5v!}-A8@?a_uIhI%1WzTI@_DDgZ{TC`;j{6yB3C}P*lWd zyXZBMB{Hzk*B-qVLNFTX`(AGGC}DrGWmdFWS(dxlogU=Mwe0W8ERZI`niYIteIM(M zG67e*z`QDd>8Y86*5NMVl2L=ftT{`qG~h3_fgWt)Es=lMdqRCIq?_8ICR{B@SrWdW z=Pv9|%{GJeJ34ho5ddCqlqn{~4dwF+? z!I7vMHj$Cc7<~Z*=D|$tBVYM@DHKh_gY3fsFrg7lMob53A`d%7r78FNIgMRi`KJ7! zZ}zf%`L4Xuhgv2|w~{-Hot>V}%Y(4P33?k5d==hMK}YH9^bCGdtFMH{Ihq7Ip3Jm< zuU%-E=sz^lF<=PNS3NSia3_7loZ5K(KO~!o?zwhT0d&qrw&=BI(ta)5umDe5{e*M& z1m3y7WKQ9fW4@3Eq|tVeKIae2!+5)6pq=`Mo%orx<+`gJt-bFeGL~63ixz=~swGt-o`w!%Zt-$o4G&#_W#+_{|fT+Z_#PmiCq`%peUVWiPw#}R;K)FxgL&#iV< zMkV7$CstqDF=Rgb@eLm`B-_59!$7aL`DOvj=opO$X+pkokS2^)a-em z-Nc^Nkuvt%mQ&`be?E0iWgZ@_xFdOW6%|VcIJew$;SX#^3s{k1jsXF_dCK9m=j@=$ zVEi)H&G3va%%x78U!QZe27b}5oAODTotb2vt$xx@pWE)jL>-A-MKj&hr+1!Eo(ni% 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+import cv2 +from PIL import Image + + +def resize_image(image, width, height): + """ + Resize the given image to specified width and height. + + :param image: An image to resize. + :param width: Width of the resized image. + :param height: Height of the resized image. + :return: Resized image. + """ + return cv2.resize(image, (width, height)) + + +def convert_bgr_to_rgb(image): + """ + Convert the BGR format image to RGB format using OpenCV. + + :param image: An image to convert. + :return: RGB image. + """ + return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) From 4c9ae6e40d4cba280794e59fe1b6ff8a4d77a123 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 02:44:51 +0900 Subject: [PATCH 11/34] refactor: Refinement of each class's functions and logic --- src/face_tagger/classifier.py | 29 +++++++++++++++++++++------- src/face_tagger/detector.py | 36 ++++++++++++++++++++++------------- src/face_tagger/embedder.py | 25 ++++++++++++------------ 3 files changed, 58 insertions(+), 32 deletions(-) diff --git a/src/face_tagger/classifier.py b/src/face_tagger/classifier.py index 459369b..457360f 100644 --- a/src/face_tagger/classifier.py +++ b/src/face_tagger/classifier.py @@ -6,23 +6,38 @@ class Classifier: """ Class for face classification. """ + def __init__(self): """ Constructor of Classifier class. """ - pass - def classify_faces(self, face_embeddings): + def convert_to_numpy(self, face_embeddings): + """ + Convert embeddings to numpy format. + + :param face_embeddings: Embeddings to convert. + :return: Numpy format embeddings. + """ + return torch.stack(face_embeddings).view(len(face_embeddings), -1).detach().numpy() + + def cluster_embeddings(self, embeddings_np): """ Cluster embeddings using HDBSCAN. - :param face_embeddings: Embeddings to cluster. + :param embeddings_np: Numpy format embeddings to cluster. :return: Cluster labels. """ - - # Cluster embeddings using HDBSCAN. - embeddings_np = torch.stack(face_embeddings).view(len(face_embeddings), -1).detach().numpy() hdbscan_cluster = hdbscan.HDBSCAN(min_cluster_size=2).fit(embeddings_np) - return hdbscan_cluster.labels_ + + def classify_faces(self, face_embeddings): + """ + Classify faces using clustering. + + :param face_embeddings: Embeddings to classify. + :return: Cluster labels. + """ + embeddings_np = self.convert_to_numpy(face_embeddings) + return self.cluster_embeddings(embeddings_np) diff --git a/src/face_tagger/detector.py b/src/face_tagger/detector.py index 15d584f..10ef0d8 100644 --- a/src/face_tagger/detector.py +++ b/src/face_tagger/detector.py @@ -10,25 +10,35 @@ def __init__(self): """ Constructor of Detector class. """ - self.face_detector = MTCNN() - def detect_face_and_crop(self, image): + def detect_face(self, image): """ - Detects faces in an image and returns cropped face images. + Detects faces in an image. :param image: Image to detect faces. - :return: Cropped face images. + :return: Detected faces with their bounding boxes. """ - # Face detection using MTCNN. - faces = self.face_detector.detect_faces(image) + return self.face_detector.detect_faces(image) - # Crop face areas in the image. - cropped_faces = [] - for face in faces: - x, y, width, height = face['box'] - cropped_face = image[y:y + height, x:x + width] - cropped_faces.append(cropped_face) + def crop(self, image, face): + """ + Crops the face area from the image. + + :param image: Image from which to crop the face. + :param face: Detected face with bounding box. + :return: Cropped face image. + """ + x, y, width, height = face['box'] + return image[y:y + height, x:x + width] - return cropped_faces + def detect_face_and_crop(self, image): + """ + Detects faces in an image and returns cropped face images. + + :param image: Image to detect faces. + :return: List of cropped face images. + """ + faces = self.detect_face(image) + return [self.crop(image, face) for face in faces] diff --git a/src/face_tagger/embedder.py b/src/face_tagger/embedder.py index 5ef240b..426fc25 100644 --- a/src/face_tagger/embedder.py +++ b/src/face_tagger/embedder.py @@ -1,8 +1,7 @@ -import cv2 import torch import torchvision.transforms as transforms -from PIL import Image from facenet_pytorch import InceptionResnetV1 +from .utils import resize_image, convert_bgr_to_rgb class Embedder: @@ -16,11 +15,19 @@ def __init__(self, use_gpu=False): :param use_gpu: Use GPU or not. """ - self.device = torch.device('cuda' if use_gpu and torch.cuda.is_available() else 'cpu') self.resnet = InceptionResnetV1(pretrained='vggface2').eval().to(self.device) self.transform = transforms.ToTensor() + def prepare_image_tensor(self, face_image): + """ + Convert the image to tensor format and add batch dimension. + + :param face_image: An image to process. + :return: Processed image tensor. + """ + return self.transform(face_image).unsqueeze(0).to(self.device) + def compute_embeddings(self, face_image): """ Compute embeddings of an image. @@ -28,15 +35,9 @@ def compute_embeddings(self, face_image): :param face_image: An image to compute embeddings. :return: Embeddings of an image. """ - - # Resize the image to 160x160. - face_image = cv2.resize(face_image, (160, 160)) - - # Convert the image to RGB. - face_image = Image.fromarray(cv2.cvtColor(face_image, cv2.COLOR_BGR2RGB)) - - # Convert the image to tensor and add a batch dimension. - img_tensor = self.transform(face_image).unsqueeze(0).to(self.device) + face_image = resize_image(face_image, 160, 160) + face_image = convert_bgr_to_rgb(face_image) + img_tensor = self.prepare_image_tensor(face_image) # Compute embeddings. img_embedding = self.resnet(img_tensor) From 620db7f241f4499b2945718f20884710c4f68a38 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 02:47:24 +0900 Subject: [PATCH 12/34] refactor: Refinement of class functions and logic, preventing log outputs from MTCNN --- src/face_tagger/face_tagger.py | 98 +++++++++++++++++++++------------- 1 file changed, 62 insertions(+), 36 deletions(-) diff --git a/src/face_tagger/face_tagger.py b/src/face_tagger/face_tagger.py index 596d6fb..c96b552 100644 --- a/src/face_tagger/face_tagger.py +++ b/src/face_tagger/face_tagger.py @@ -1,8 +1,10 @@ -import cv2 +import os +import sys from src.face_tagger.classifier import Classifier from src.face_tagger.detector import Detector from src.face_tagger.embedder import Embedder +from src.face_tagger.utils import resize_image class FaceTagger: @@ -13,7 +15,6 @@ class FaceTagger: def __init__(self, use_gpu=False, image_resize_factor=1.0): """ Constructor of FaceTagger class. - :param use_gpu: Use GPU or not. :param image_resize_factor: Resize factor of images. """ @@ -23,64 +24,89 @@ def __init__(self, use_gpu=False, image_resize_factor=1.0): self.classifier = Classifier() self.image_resize_factor = image_resize_factor + def detect_and_embed_faces(self, image): + """ + Detects and embeds faces in an image. + :param image: Image to detect and embed faces. + :return: Cropped faces and their embeddings. + """ + + face_embeddings = [] + cropped_faces = self.detector.detect_face_and_crop(image) + + for cropped_face in cropped_faces: + face_embedding = self.embedder.compute_embeddings(cropped_face) + face_embeddings.append(face_embedding) + + return cropped_faces, face_embeddings + + def group_and_classify(self, face_embeddings, processed_image_ids): + """ + Groups and classifies images based on the person in the image. + :param face_embeddings: Embeddings of faces. + :param processed_image_ids: Image ids of the processed images. + :return: Classified images. + """ + + classified_images = {"unclassified_images": []} + groups = self.classifier.classify_faces(face_embeddings) + + face_counts_per_image = {} + for image_id in processed_image_ids: + face_counts_per_image[image_id] = face_counts_per_image.get(image_id, 0) + 1 + + for group, image_id in zip(groups, processed_image_ids): + if group != -1: + group_key = f"group_{group + 1}" + + if group_key not in classified_images: + classified_images[group_key] = {"main": None, "others": []} + + if face_counts_per_image[image_id] == 1: + classified_images[group_key]["main"] = image_id + continue + + if image_id not in classified_images[group_key]["others"]: + classified_images[group_key]["others"].append(image_id) + + return classified_images + def classify_images_by_person(self, image_objects): """ Classifies images based on the person in the image. - :param image_objects: Images to classify. :return: Classified images. """ face_embeddings = [] processed_image_ids = [] - face_counts_per_image = {} + unclassified_images = [] - classified_images = {"unclassified_images": []} + sys.stdout = open(os.devnull, 'w') # Embedding faces in each image. for image_object in image_objects: if self.image_resize_factor != 1.0: - image = cv2.resize(image_object.image_data, ( - int(image_object.image_data.shape[1] * self.image_resize_factor), - int(image_object.image_data.shape[0] * self.image_resize_factor))) + image = resize_image(image_object.image_data, + int(image_object.image_data.shape[1] * self.image_resize_factor), + int(image_object.image_data.shape[0] * self.image_resize_factor)) else: image = image_object.image_data if image is not None: - cropped_faces = self.detector.detect_face_and_crop(image) + cropped_faces, current_face_embeddings = self.detect_and_embed_faces(image) + face_embeddings.extend(current_face_embeddings) if len(cropped_faces) == 0: # If there is no face in the image, add the image to the list of unclassified images. - classified_images["unclassified_images"].append(image_object.image_id) + unclassified_images.append(image_object.image_id) continue - face_counts_per_image[image_object.image_id] = len(cropped_faces) + processed_image_ids.extend([image_object.image_id] * len(cropped_faces)) - # Compute embeddings of cropped faces. - for cropped_face in cropped_faces: - face_embedding = self.embedder.compute_embeddings(cropped_face) - face_embeddings.append(face_embedding) - processed_image_ids.append(image_object.image_id) + sys.stdout = sys.__stdout__ - # Classifying embedded faces. - groups = self.classifier.classify_faces(face_embeddings) - - # Grouping images by person. - for group, image_id in zip(groups, processed_image_ids): - if group != -1: - group_key = f"group_{group + 1}" - - if group_key not in classified_images: - # If the group is not in the dictionary, add the group. - classified_images[group_key] = {"main": None, "others": []} - - if face_counts_per_image[image_id] == 1: - # If there is only one face in the image, the face is the main face. - classified_images[group_key]["main"] = image_id - continue - - if image_id not in classified_images[group_key]["others"]: - # If the image is not in the list of other images, add the image. - classified_images[group_key]["others"].append(image_id) + classified_images = self.group_and_classify(face_embeddings, processed_image_ids) + classified_images["unclassified_images"] = unclassified_images return classified_images From 293b079c3669a124eb7c7d69c3dd9bcf70eb74ab Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 02:48:47 +0900 Subject: [PATCH 13/34] docs: Update comments --- src/face_tagger/classifier.py | 9 ++++++--- src/face_tagger/detector.py | 9 ++++++--- src/face_tagger/embedder.py | 6 +++--- src/face_tagger/utils.py | 4 ++-- 4 files changed, 17 insertions(+), 11 deletions(-) diff --git a/src/face_tagger/classifier.py b/src/face_tagger/classifier.py index 457360f..80bb279 100644 --- a/src/face_tagger/classifier.py +++ b/src/face_tagger/classifier.py @@ -11,33 +11,36 @@ def __init__(self): """ Constructor of Classifier class. """ + pass def convert_to_numpy(self, face_embeddings): """ Convert embeddings to numpy format. - :param face_embeddings: Embeddings to convert. :return: Numpy format embeddings. """ + return torch.stack(face_embeddings).view(len(face_embeddings), -1).detach().numpy() def cluster_embeddings(self, embeddings_np): """ Cluster embeddings using HDBSCAN. - :param embeddings_np: Numpy format embeddings to cluster. :return: Cluster labels. """ + hdbscan_cluster = hdbscan.HDBSCAN(min_cluster_size=2).fit(embeddings_np) + return hdbscan_cluster.labels_ def classify_faces(self, face_embeddings): """ Classify faces using clustering. - :param face_embeddings: Embeddings to classify. :return: Cluster labels. """ + embeddings_np = self.convert_to_numpy(face_embeddings) + return self.cluster_embeddings(embeddings_np) diff --git a/src/face_tagger/detector.py b/src/face_tagger/detector.py index 10ef0d8..e6005f0 100644 --- a/src/face_tagger/detector.py +++ b/src/face_tagger/detector.py @@ -10,35 +10,38 @@ def __init__(self): """ Constructor of Detector class. """ + self.face_detector = MTCNN() def detect_face(self, image): """ Detects faces in an image. - :param image: Image to detect faces. :return: Detected faces with their bounding boxes. """ + # Face detection using MTCNN. return self.face_detector.detect_faces(image) def crop(self, image, face): """ Crops the face area from the image. - :param image: Image from which to crop the face. :param face: Detected face with bounding box. :return: Cropped face image. """ + x, y, width, height = face['box'] + return image[y:y + height, x:x + width] def detect_face_and_crop(self, image): """ Detects faces in an image and returns cropped face images. - :param image: Image to detect faces. :return: List of cropped face images. """ + faces = self.detect_face(image) + return [self.crop(image, face) for face in faces] diff --git a/src/face_tagger/embedder.py b/src/face_tagger/embedder.py index 426fc25..9ef2955 100644 --- a/src/face_tagger/embedder.py +++ b/src/face_tagger/embedder.py @@ -12,9 +12,9 @@ class Embedder: def __init__(self, use_gpu=False): """ Constructor of Embedder class. - :param use_gpu: Use GPU or not. """ + self.device = torch.device('cuda' if use_gpu and torch.cuda.is_available() else 'cpu') self.resnet = InceptionResnetV1(pretrained='vggface2').eval().to(self.device) self.transform = transforms.ToTensor() @@ -22,19 +22,19 @@ def __init__(self, use_gpu=False): def prepare_image_tensor(self, face_image): """ Convert the image to tensor format and add batch dimension. - :param face_image: An image to process. :return: Processed image tensor. """ + return self.transform(face_image).unsqueeze(0).to(self.device) def compute_embeddings(self, face_image): """ Compute embeddings of an image. - :param face_image: An image to compute embeddings. :return: Embeddings of an image. """ + face_image = resize_image(face_image, 160, 160) face_image = convert_bgr_to_rgb(face_image) img_tensor = self.prepare_image_tensor(face_image) diff --git a/src/face_tagger/utils.py b/src/face_tagger/utils.py index 16fb5a0..b6058a7 100644 --- a/src/face_tagger/utils.py +++ b/src/face_tagger/utils.py @@ -5,20 +5,20 @@ def resize_image(image, width, height): """ Resize the given image to specified width and height. - :param image: An image to resize. :param width: Width of the resized image. :param height: Height of the resized image. :return: Resized image. """ + return cv2.resize(image, (width, height)) def convert_bgr_to_rgb(image): """ Convert the BGR format image to RGB format using OpenCV. - :param image: An image to convert. :return: RGB image. """ + return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) From b2af636a6812c2a60f909aa092a44b32555970c7 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 04:00:57 +0900 Subject: [PATCH 14/34] chore: Add images for testing --- tests/resources/one_person_1.jpg | Bin 0 -> 353368 bytes tests/resources/one_person_2.jpg | Bin 0 -> 241529 bytes tests/resources/one_person_3.jpg | Bin 0 -> 250228 bytes tests/resources/one_person_4.jpg | Bin 0 -> 65287 bytes tests/resources/one_person_5.jpg | Bin 0 -> 816155 bytes tests/resources/one_person_6.jpg | Bin 0 -> 113595 bytes tests/resources/seven_people.jpg | Bin 0 -> 213267 bytes tests/resources/two_people.jpg | Bin 0 -> 252228 bytes 8 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 tests/resources/one_person_1.jpg create mode 100644 tests/resources/one_person_2.jpg create mode 100644 tests/resources/one_person_3.jpg create mode 100644 tests/resources/one_person_4.jpg create mode 100644 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0 HcmV?d00001 From c34f7fc0619188a473dda6eadff5729b19dc8eba Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 11:51:08 +0900 Subject: [PATCH 15/34] feature: Add minimum faces to be grouped and minimum similarity face count value in Classifier class --- src/face_tagger/classifier.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/src/face_tagger/classifier.py b/src/face_tagger/classifier.py index 80bb279..c340bb4 100644 --- a/src/face_tagger/classifier.py +++ b/src/face_tagger/classifier.py @@ -7,12 +7,15 @@ class Classifier: Class for face classification. """ - def __init__(self): + def __init__(self, min_faces_to_be_group=3, min_similarity_face_count=2): """ Constructor of Classifier class. + :param min_faces_to_be_group: Minimum number of faces required to be classified as a group. + :param min_similarity_Face_count: Minimum number of similar faces required to be included in a group. """ - pass + self.min_faces_to_be_group = min_faces_to_be_group + self.min_similarity_face_count = min_similarity_face_count def convert_to_numpy(self, face_embeddings): """ @@ -30,7 +33,8 @@ def cluster_embeddings(self, embeddings_np): :return: Cluster labels. """ - hdbscan_cluster = hdbscan.HDBSCAN(min_cluster_size=2).fit(embeddings_np) + hdbscan_cluster = hdbscan.HDBSCAN(min_samples=self.min_similarity_face_count, + min_cluster_size=self.min_faces_to_be_group).fit(embeddings_np) return hdbscan_cluster.labels_ From b78e61bf72bc4f5fec431cf7ec2776ce814a5349 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 11:53:47 +0900 Subject: [PATCH 16/34] feature: Add minimum faces to be grouped and minimum similarity face count value in FaceTagger constructor parameter --- src/face_tagger/face_tagger.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/face_tagger/face_tagger.py b/src/face_tagger/face_tagger.py index c96b552..81566fa 100644 --- a/src/face_tagger/face_tagger.py +++ b/src/face_tagger/face_tagger.py @@ -12,7 +12,7 @@ class FaceTagger: Main class of the face tagger module. """ - def __init__(self, use_gpu=False, image_resize_factor=1.0): + def __init__(self, use_gpu=False, image_resize_factor=1.0, min_faces_to_be_group=3, min_similarity_face_count=2): """ Constructor of FaceTagger class. :param use_gpu: Use GPU or not. @@ -21,7 +21,8 @@ def __init__(self, use_gpu=False, image_resize_factor=1.0): self.detector = Detector() self.embedder = Embedder(use_gpu) - self.classifier = Classifier() + self.classifier = Classifier(min_faces_to_be_group=min_faces_to_be_group, + min_similarity_face_count=min_similarity_face_count) self.image_resize_factor = image_resize_factor def detect_and_embed_faces(self, image): From e963705fdfbc0812ae91e382bbf180a40499249e Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 11:54:24 +0900 Subject: [PATCH 17/34] fix: Resolve the issue of images not being properly added to 'unclassified_images'. --- src/face_tagger/face_tagger.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/src/face_tagger/face_tagger.py b/src/face_tagger/face_tagger.py index 81566fa..d4d4279 100644 --- a/src/face_tagger/face_tagger.py +++ b/src/face_tagger/face_tagger.py @@ -63,12 +63,14 @@ def group_and_classify(self, face_embeddings, processed_image_ids): if group_key not in classified_images: classified_images[group_key] = {"main": None, "others": []} - if face_counts_per_image[image_id] == 1: + if face_counts_per_image[image_id] == 1 and classified_images[group_key]["main"] is None: classified_images[group_key]["main"] = image_id continue if image_id not in classified_images[group_key]["others"]: classified_images[group_key]["others"].append(image_id) + else: + classified_images["unclassified_images"].append(image_id) return classified_images @@ -108,6 +110,6 @@ def classify_images_by_person(self, image_objects): sys.stdout = sys.__stdout__ classified_images = self.group_and_classify(face_embeddings, processed_image_ids) - classified_images["unclassified_images"] = unclassified_images + classified_images["unclassified_images"].extend(unclassified_images) return classified_images From 7a8ef502d47c62d00b3d5343ec56b94ccc0a5298 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:24:08 +0900 Subject: [PATCH 18/34] feature: Remove duplicated image id in 'unclassified_images' --- src/face_tagger/face_tagger.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/src/face_tagger/face_tagger.py b/src/face_tagger/face_tagger.py index d4d4279..daa601d 100644 --- a/src/face_tagger/face_tagger.py +++ b/src/face_tagger/face_tagger.py @@ -110,6 +110,7 @@ def classify_images_by_person(self, image_objects): sys.stdout = sys.__stdout__ classified_images = self.group_and_classify(face_embeddings, processed_image_ids) - classified_images["unclassified_images"].extend(unclassified_images) + classified_images["unclassified_images"] = list( + set(classified_images["unclassified_images"]).union(set(unclassified_images))) return classified_images From 7b5c25873fdc855fc284b2bd86b12e5de7efbd29 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:24:40 +0900 Subject: [PATCH 19/34] test: Add unit test for FaceTagger, Detector, Embedder, Classifier class --- tests/face_tagger_unit_test.py | 105 +++++++++++++++++++++++++++++++++ 1 file changed, 105 insertions(+) create mode 100644 tests/face_tagger_unit_test.py diff --git a/tests/face_tagger_unit_test.py b/tests/face_tagger_unit_test.py new file mode 100644 index 0000000..5f6ba70 --- /dev/null +++ b/tests/face_tagger_unit_test.py @@ -0,0 +1,105 @@ +import os +import sys +import unittest + +import cv2 +import numpy as np +import torch + +from src.face_tagger import FaceTagger +from src.face_tagger.classifier import Classifier +from src.face_tagger.detector import Detector +from src.face_tagger.embedder import Embedder + + +class TestEmbedder(unittest.TestCase): + + def setUp(self): + self.embedder = Embedder(use_gpu=False) + self.sample_image = cv2.imread("resources/lenna.png") + + def test_prepare_image_tensor(self): + tensor = self.embedder.prepare_image_tensor(self.sample_image) + self.assertIsInstance(tensor, torch.Tensor) + + def test_compute_embeddings(self): + embedding = self.embedder.compute_embeddings(self.sample_image) + self.assertIsInstance(embedding, torch.Tensor) + + +class TestDetector(unittest.TestCase): + + def setUp(self): + self.detector = Detector() + + def test_detect_one_face(self): + test_cases_one = [ + "resources/one_person_1.jpg", + "resources/one_person_2.jpg", + "resources/one_person_3.jpg", + "resources/one_person_4.jpg", + "resources/one_person_5.jpg", + "resources/one_person_6.jpg" + ] + + test_cases_multiple = { + "resources/two_people.jpg": 2, + "resources/seven_people.jpg": 7 + } + + for file_path in test_cases_one: + sys.stdout = open(os.devnull, 'w') + face = self.detector.detect_face(cv2.imread(file_path)) + sys.stdout = sys.__stdout__ + self.assertEqual(len(face), 1) + + for file_path, expected_faces in test_cases_multiple.items(): + sys.stdout = open(os.devnull, 'w') + faces = self.detector.detect_face(cv2.imread(file_path)) + sys.stdout = sys.__stdout__ + self.assertEqual(len(faces), expected_faces) + + +class TestClassifier(unittest.TestCase): + + def setUp(self): + self.classifier = Classifier() + self.sample_embeddings = [torch.rand((512,)) for _ in range(5)] + + def test_convert_to_numpy(self): + np_embeddings = self.classifier.convert_to_numpy(self.sample_embeddings) + self.assertIsInstance(np_embeddings, np.ndarray) + + def test_cluster_embeddings(self): + np_embeddings = self.classifier.convert_to_numpy(self.sample_embeddings) + labels = self.classifier.cluster_embeddings(np_embeddings) + self.assertEqual(len(labels), len(self.sample_embeddings)) + + def test_classify_faces(self): + labels = self.classifier.classify_faces(self.sample_embeddings) + self.assertEqual(len(labels), len(self.sample_embeddings)) + + +class TestFaceTagger(unittest.TestCase): + + def setUp(self): + self.face_tagger = FaceTagger(use_gpu=False) + + def test_detect_and_embed_single_faces(self): + for i in range(1, 3): + image = cv2.imread(f"resources/one_person_{i}.jpg") + cropped_faces, face_embeddings = self.face_tagger.detect_and_embed_faces(image) + self.assertEqual(len(cropped_faces), 1) + self.assertEqual(len(face_embeddings), 1) + + def test_detect_and_embed_multiple_faces(self): + test_cases = { + "resources/two_people.jpg": 2, + "resources/seven_people.jpg": 7, + } + + for file_path, expected_faces in test_cases.items(): + image = cv2.imread(file_path) + cropped_faces, face_embeddings = self.face_tagger.detect_and_embed_faces(image) + self.assertEqual(len(cropped_faces), expected_faces) + self.assertEqual(len(face_embeddings), expected_faces) From 474bcc6477f9027d3ec4a3c589bdf62cc4809191 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:24:56 +0900 Subject: [PATCH 20/34] test: Add e2e test for FaceTagger library --- tests/face_tagger_e2e_test.py | 38 +++++++++++++++++++++++++++++++++++ 1 file changed, 38 insertions(+) create mode 100644 tests/face_tagger_e2e_test.py diff --git a/tests/face_tagger_e2e_test.py b/tests/face_tagger_e2e_test.py new file mode 100644 index 0000000..690c8d6 --- /dev/null +++ b/tests/face_tagger_e2e_test.py @@ -0,0 +1,38 @@ +import unittest + +import cv2 + +from src.face_tagger import FaceTagger + + +class TestFaceTagger(unittest.TestCase): + def setUp(self): + self.face_tagger = FaceTagger(use_gpu=False, min_faces_to_be_group=2, min_similarity_face_count=1) + + def test_classify_images_by_person(self): + image_objects = [] + + image_data_map = { + "one_person_1.jpg": 3, + "one_person_3.jpg": 2, + "two_people.jpg": 1 + } + + for image_name, count in image_data_map.items(): + image_data = cv2.imread(f"resources/{image_name}") + + for i in range(count): + image_obj = type("ImageObject", (object,), { + "image_data": image_data, + "image_id": f"{image_name.split('.')[0]}_{i + 1}" + }) + image_objects.append(image_obj) + + result = self.face_tagger.classify_images_by_person(image_objects) + + self.assertIsInstance(result, dict) + self.assertIn("unclassified_images", result) + self.assertEqual(len(result["unclassified_images"]), 1) + self.assertEqual(len(result["group_1"]["others"]), 2) + self.assertEqual(len(result["group_2"]["others"]), 1) + From c9cfd9af38cdee024e920aa3a28101e8c0cc5274 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:25:17 +0900 Subject: [PATCH 21/34] refactor: Rename test_face_tagger.py to face_tagger_unit_test.py --- tests/test_face_tagger.py | 1 - 1 file changed, 1 deletion(-) delete mode 100644 tests/test_face_tagger.py diff --git a/tests/test_face_tagger.py b/tests/test_face_tagger.py deleted file mode 100644 index 8b13789..0000000 --- a/tests/test_face_tagger.py +++ /dev/null @@ -1 +0,0 @@ - From 89e3889ec073afa7274a6509b3ceef04ce15ed02 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:26:41 +0900 Subject: [PATCH 22/34] chore: Update requirements.txt --- requirements.txt | Bin 6278 -> 2394 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/requirements.txt b/requirements.txt index 3c24e14f0d819b8850be5ce104604ccac1189a00..6919fa540750b6c25a36e555d855c43afd03507f 100644 GIT binary patch literal 2394 zcma);OK;mi421Vwpg+YyEa%Z2dg`q}fdW1BSjh4-aU@5U^5~CmJ0B@}?Idjj!wDjC zhr{7;mEXV0G)=p-Nu#t)PwAsR<8+eF^gT`Q)4NnE+ND0#ikGR?U-Ny|g|a4=RVh}b zm113L^w}s6taHma5hhrb;;k~)X`wIiLRAW3oLJ`NkhR)Z>cp!SUYl<9Y@<^@4TH0s zD)e=pl|`#`W4IsmoIU~(Mxd02!|78+>GHyAep2t9_&2H+(IQNq=#01ASbC0?j zI2}gIp&#!hSbtHh)qH2F^DyvsZq$K6Wc2F$o3fd6t`=Fhin4PtyJPp>>UkyftP62x z>5hC*eRw<`Xh8K^egHe)HNHpA?X}6no_V@{jn2-6Ql+{~?LMDV$E{Az=f(@D5 zTy|EUe!=DI)5b&WMJZjGpR4P4llS#i&o}y@E9b{nC3|wKej8O{zU&V<@No?H##WPM zA3!3`M&Y<~n+&Qj`&!sU!6qXZ=4jjwy>RA(TgcA+a1Y(77SV3VK*fo$1Mzvz-!~6j zSAiSB_l(}Ij5j;7mUi5CBV&XI-5bZg@yx^NkByIG?}XrfaW~~H-AS2a*Klv)r%oN# z;)L6#`bp)PsYkcIJ+9yDnImQ6@>0xsx3%&WKSTe^edmYg7Y9E0SDnbieavA!>=bON 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a/tests/face_tagger_e2e_test.py b/tests/face_tagger_e2e_test.py index 690c8d6..d883c13 100644 --- a/tests/face_tagger_e2e_test.py +++ b/tests/face_tagger_e2e_test.py @@ -1,9 +1,12 @@ +import os import unittest import cv2 from src.face_tagger import FaceTagger +BASE_DIR = os.path.dirname(os.path.abspath(__file__)) + class TestFaceTagger(unittest.TestCase): def setUp(self): @@ -19,7 +22,7 @@ def test_classify_images_by_person(self): } for image_name, count in image_data_map.items(): - image_data = cv2.imread(f"resources/{image_name}") + image_data = cv2.imread(os.path.join(BASE_DIR, "resources", image_name)) for i in range(count): image_obj = type("ImageObject", (object,), { @@ -35,4 +38,3 @@ def test_classify_images_by_person(self): self.assertEqual(len(result["unclassified_images"]), 1) self.assertEqual(len(result["group_1"]["others"]), 2) self.assertEqual(len(result["group_2"]["others"]), 1) - diff --git a/tests/face_tagger_unit_test.py b/tests/face_tagger_unit_test.py index 5f6ba70..fd36dcd 100644 --- a/tests/face_tagger_unit_test.py +++ b/tests/face_tagger_unit_test.py @@ -11,12 +11,14 @@ from src.face_tagger.detector import Detector from src.face_tagger.embedder import Embedder +BASE_DIR = os.path.dirname(os.path.abspath(__file__)) + class TestEmbedder(unittest.TestCase): def setUp(self): self.embedder = Embedder(use_gpu=False) - self.sample_image = cv2.imread("resources/lenna.png") + self.sample_image = cv2.imread(os.path.join(BASE_DIR, "resources", "one_person_1.jpg")) def test_prepare_image_tensor(self): tensor = self.embedder.prepare_image_tensor(self.sample_image) @@ -34,17 +36,17 @@ def setUp(self): def test_detect_one_face(self): test_cases_one = [ - "resources/one_person_1.jpg", - "resources/one_person_2.jpg", - "resources/one_person_3.jpg", - "resources/one_person_4.jpg", - "resources/one_person_5.jpg", - "resources/one_person_6.jpg" + os.path.join(BASE_DIR, "resources", "one_person_1.jpg"), + os.path.join(BASE_DIR, "resources", "one_person_2.jpg"), + os.path.join(BASE_DIR, "resources", "one_person_3.jpg"), + os.path.join(BASE_DIR, "resources", "one_person_4.jpg"), + os.path.join(BASE_DIR, "resources", "one_person_5.jpg"), + os.path.join(BASE_DIR, "resources", "one_person_6.jpg") ] test_cases_multiple = { - "resources/two_people.jpg": 2, - "resources/seven_people.jpg": 7 + os.path.join(BASE_DIR, "resources", "two_people.jpg"): 2, + os.path.join(BASE_DIR, "resources", "seven_people.jpg"): 7 } for file_path in test_cases_one: @@ -87,15 +89,15 @@ def setUp(self): def test_detect_and_embed_single_faces(self): for i in range(1, 3): - image = cv2.imread(f"resources/one_person_{i}.jpg") + image = cv2.imread(os.path.join(BASE_DIR, "resources", f"one_person_{i}.jpg")) cropped_faces, face_embeddings = self.face_tagger.detect_and_embed_faces(image) self.assertEqual(len(cropped_faces), 1) self.assertEqual(len(face_embeddings), 1) def test_detect_and_embed_multiple_faces(self): test_cases = { - "resources/two_people.jpg": 2, - "resources/seven_people.jpg": 7, + os.path.join(BASE_DIR, "resources", "two_people.jpg"): 2, + os.path.join(BASE_DIR, "resources", "seven_people.jpg"): 7, } for file_path, expected_faces in test_cases.items(): From 338b2491a553c030bef2d8fb0808316f1a4b0aef Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 12:49:16 +0900 Subject: [PATCH 24/34] chore: Add unit test and e2e test logic for each yml file --- .github/workflows/lib-e2e-test.yml | 4 ++-- .github/workflows/lib-unit-test.yml | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/.github/workflows/lib-e2e-test.yml b/.github/workflows/lib-e2e-test.yml index 9dcabe1..674f6e3 100644 --- a/.github/workflows/lib-e2e-test.yml +++ b/.github/workflows/lib-e2e-test.yml @@ -18,6 +18,6 @@ jobs: run: | pip install -r requirements.txt - - name: Run tests + - name: Run e2e tests run: | - pytest \ No newline at end of file + pytest tests/face_tagger_e2e_test.py \ No newline at end of file diff --git a/.github/workflows/lib-unit-test.yml b/.github/workflows/lib-unit-test.yml index b81a9dd..6470a5e 100644 --- a/.github/workflows/lib-unit-test.yml +++ b/.github/workflows/lib-unit-test.yml @@ -18,6 +18,6 @@ jobs: run: | pip install -r requirements.txt - - name: Run tests + - name: Run unit tests run: | - pytest \ No newline at end of file + pytest tests/face_tagger_unit_test.py \ No newline at end of file From d44b12fb2b1290ce5d7f788d0c96fdd9e680b719 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 13:24:47 +0900 Subject: [PATCH 25/34] feature: Add modules in __init__.py --- src/face_tagger/__init__.py | 4 ++++ src/face_tagger/models/__init__.py | 1 + 2 files changed, 5 insertions(+) diff --git a/src/face_tagger/__init__.py b/src/face_tagger/__init__.py index e12a454..8115396 100644 --- a/src/face_tagger/__init__.py +++ b/src/face_tagger/__init__.py @@ -1 +1,5 @@ from .face_tagger import FaceTagger +from .classifier import Classifier +from .detector import Detector +from .embedder import Embedder +from .utils import resize_image, convert_bgr_to_rgb, bytes_to_cvimage diff --git a/src/face_tagger/models/__init__.py b/src/face_tagger/models/__init__.py index e69de29..bbe8bb2 100644 --- a/src/face_tagger/models/__init__.py +++ b/src/face_tagger/models/__init__.py @@ -0,0 +1 @@ +from .image_object import ImageObject From 0439f475d14957ece8fddb5455c2bce0382b81bf Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 13:25:18 +0900 Subject: [PATCH 26/34] feature: Add change bytes to opencv image function --- src/face_tagger/utils.py | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/src/face_tagger/utils.py b/src/face_tagger/utils.py index b6058a7..3d36b80 100644 --- a/src/face_tagger/utils.py +++ b/src/face_tagger/utils.py @@ -1,4 +1,5 @@ import cv2 +import numpy as np from PIL import Image @@ -22,3 +23,13 @@ def convert_bgr_to_rgb(image): """ return Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) + + +def bytes_to_cvimage(byte_stream): + """ + Convert byte stream to OpenCV image format. + :param byte_stream: Bytes representing image data. + :return: OpenCV format image. + """ + + return cv2.imdecode(np.frombuffer(byte_stream, np.uint8), cv2.IMREAD_COLOR) From b75376c408d07d4d039f2e629e8158b030120a9e Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 14:12:40 +0900 Subject: [PATCH 27/34] docs: Update README.md --- README.md | 97 ++++++++++++++++++++++++++++++++++++++++++++++++++++--- 1 file changed, 93 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 95b84de..cadde7a 100644 --- a/README.md +++ b/README.md @@ -8,6 +8,8 @@ Face Tagger is a Python library designed to classify photos containing specific - **Face Recognition**: Identify and differentiate faces in multiple images. - **Photo Classification**: Group photos based on the identified individual. +- **GPU Acceleration**: Optimized performance using GPU, if available. +- **Easy Integration**: Simple APIs for seamless integration into various applications.
    @@ -21,21 +23,108 @@ pip install face-tagger
    +## Dependencies + +Face Tagger relies on several key libraries to function effectively. Understanding these dependencies can provide insights into the library's internal workings and can be beneficial for troubleshooting. Here are the primary dependencies: + +- **OpenCV (cv2)**: Used for image processing tasks like reading and preprocessing images. +- **Torch (torch)**: The primary deep learning framework employed for face embedding. +- **MTCNN**: Essential for the detection of faces within images. + +Make sure to have these dependencies properly installed or ensure they are present in your environment when working with Face Tagger. For a comprehensive list and exact versions, please refer to the `requirements.txt` file. + +
    + +## How it Works + +Face Tagger follows a systematic process to classify images: + +1. **Image Loading** + - Uses standard Python libraries, typically OpenCV (`cv2`), to read and preprocess images. + +2. **Face Detection** + - Utilizes the MTCNN (Multi-task Cascaded Convolutional Networks) library for detecting faces in images. + +3. **Embedding Computation** + - Employs the FaceNet model, often via the `torch` library, to compute a vector (embedding) for each + detected face. + +4. **Face Classification** + - Uses a HDBSCAN clustering algorithm to group similar face embeddings together. + +5. **Result Compilation** + - Once the faces are classified, the result is compiled and presented in a structured format that informs which + images contain which individual(s). + +
    + ## Usage + +To utilize the Face Tagger library, follow these steps: + +1. **Define an image generator**: + The generator function allows you to loop through all images in a specified directory and create `ImageObject` + instances for each one. + ```python -# Sample Code +def image_generator(image_dir): + for filename in os.listdir(image_dir): + img = cv2.imread(os.path.join(image_dir, filename)) + if img is not None: + yield ImageObject(filename, img) ``` -(Note: The above code is just a fictional example and may not represent the actual usage of the Face Tagger library.) +(Note: You don't necessarily need to use a generator for image_objects. You can also create ImageObject list from loaded +images in an array and pass them.) + +Here is the representation of the `ImageObject` class: + +> #### Attributes: +> - **image_id**: A unique identifier for the image. +> - **image_data**: Actual image data, loaded using OpenCV. +> +> #### Example: +> ```python +> img_obj = ImageObject(image_id="unique_id_123", image_data=loaded_image_data) +> ``` + +2. **Initialize the Face Tagger**: + Here, you can set various parameters like `use_gpu`, `image_resize_factor`, `min_faces_to_be_group`, + and `min_similarity_face_count`. + +```python +face_tagger = FaceTagger( + use_gpu=False, + image_resize_factor=1.0, + min_faces_to_be_group=2, + min_similarity_face_count=1 +) +``` + +3. **Classify images by person**: + Now, use the `classify_images_by_person` method of the `face_tagger` instance and pass the `image_objects` from the + generator function to classify the images. + +```python +result = face_tagger.classify_images_by_person(image_objects=image_generator("path_to_images_directory")) +print(result) +``` + +Replace `path_to_images_directory` with the path to your image directory. + +--- + +With these steps, you can effectively utilize the Face Tagger library to classify images based on the individuals they +contain.
    ## Contributing -Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. +Pull requests are welcome. For major changes, please open an [issue]('https://github.com/Face-Tagger/facetagger-lib/issues/new') first to discuss what you would like to change.
    ## License -[MIT](https://choosealicense.com/licenses/mit/) \ No newline at end of file +[MIT](https://github.com/Face-Tagger/facetagger-lib/blob/main/LICENSE) From 27aa06246fadf0bc60a58b4f46cbb0680d326e14 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 14:16:42 +0900 Subject: [PATCH 28/34] chore: Update pip before install dependencies --- .github/workflows/lib-deploy.yml | 1 + .github/workflows/lib-e2e-test.yml | 1 + .github/workflows/lib-unit-test.yml | 1 + 3 files changed, 3 insertions(+) diff --git a/.github/workflows/lib-deploy.yml b/.github/workflows/lib-deploy.yml index c33b646..fdbc1ac 100644 --- a/.github/workflows/lib-deploy.yml +++ b/.github/workflows/lib-deploy.yml @@ -26,6 +26,7 @@ jobs: - name: Install dependencies run: + pip install --upgrade pip pip install build --user - name: Build a binary wheel and a source tarball diff --git a/.github/workflows/lib-e2e-test.yml b/.github/workflows/lib-e2e-test.yml index 674f6e3..d710e72 100644 --- a/.github/workflows/lib-e2e-test.yml +++ b/.github/workflows/lib-e2e-test.yml @@ -16,6 +16,7 @@ jobs: - name: Install dependencies run: | + pip install --upgrade pip pip install -r requirements.txt - name: Run e2e tests diff --git a/.github/workflows/lib-unit-test.yml b/.github/workflows/lib-unit-test.yml index 6470a5e..622298d 100644 --- a/.github/workflows/lib-unit-test.yml +++ b/.github/workflows/lib-unit-test.yml @@ -16,6 +16,7 @@ jobs: - name: Install dependencies run: | + pip install --upgrade pip pip install -r requirements.txt - name: Run unit tests From 7d8cf22f9a6fd3a7951a27f4968b8638d2f6e40c Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 14:56:45 +0900 Subject: [PATCH 29/34] chore: Define Python runtime environment and change tensorflow-intel to tensorflow-cpu --- .github/workflows/lib-deploy.yml | 2 +- .github/workflows/lib-e2e-test.yml | 5 +++++ .github/workflows/lib-unit-test.yml | 5 +++++ requirements.txt | Bin 2394 -> 2390 bytes 4 files changed, 11 insertions(+), 1 deletion(-) diff --git a/.github/workflows/lib-deploy.yml b/.github/workflows/lib-deploy.yml index fdbc1ac..785c28d 100644 --- a/.github/workflows/lib-deploy.yml +++ b/.github/workflows/lib-deploy.yml @@ -26,7 +26,7 @@ jobs: - name: Install dependencies run: - pip install --upgrade pip + pip install --upgrade pip pip install build --user - name: Build a binary wheel and a source tarball diff --git a/.github/workflows/lib-e2e-test.yml b/.github/workflows/lib-e2e-test.yml index d710e72..ad1c835 100644 --- a/.github/workflows/lib-e2e-test.yml +++ b/.github/workflows/lib-e2e-test.yml @@ -14,6 +14,11 @@ jobs: - name: Checkout code uses: actions/checkout@v2 + - name: Setup Python + uses: actions/setup-python@v2 + with: + python-version: '3.11' + - name: Install dependencies run: | pip install --upgrade pip diff --git a/.github/workflows/lib-unit-test.yml b/.github/workflows/lib-unit-test.yml index 622298d..71480cc 100644 --- a/.github/workflows/lib-unit-test.yml +++ b/.github/workflows/lib-unit-test.yml @@ -14,6 +14,11 @@ jobs: - name: Checkout code uses: actions/checkout@v2 + - name: Setup Python + uses: actions/setup-python@v2 + with: + python-version: '3.11' + - name: Install dependencies run: | pip install --upgrade pip diff --git a/requirements.txt b/requirements.txt index 6919fa540750b6c25a36e555d855c43afd03507f..9c211dec2a931c4bb26666c8241c794af4000b67 100644 GIT binary patch delta 18 acmca5bWLc(GIrKvh60At&Fk4$GXelZVg{4| delta 26 icmca6bW3Q%GIq{PhCGH6hE#@}$@c8po3F7qFaiL1YzS-s From 450f8c47b5aa9011791da8872bc64c72dc585390 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 15:19:12 +0900 Subject: [PATCH 30/34] chore: Update requirements.txt --- requirements.txt | Bin 2390 -> 2132 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/requirements.txt b/requirements.txt index 9c211dec2a931c4bb26666c8241c794af4000b67..4aff17fa313ce83e82736e6e7669f9712bc2a032 100644 GIT binary patch delta 107 zcmca6bVXo77rQxw9)l5s(Zqi1$sCMIlXo%tF&a{%17W+{q@($eGEI$56tM%8)bJo?UzLHTH9p4{#I# JO)=(F1^|Dq9?}2+ delta 333 zcmca2a7}1J7pp0Q9)tPBiPo0M3^@#$49N`H47NaM0Tea_Nipy;Z~;a0fwK7wMGT1y zxj+n3VE~jh0b;X>$JMPtEe?z6+pGRKx^|EQh>U17>eQ68w2eznD{c7(P*+Q<9kN4$+}GTj0Tf)nF1LN zC+}x+1hN^K6&Z~;D>IifDuYy;fZbC7G@}%3dk)wvP#A#RY&v;9%YR10>7h8CjDV o3K&W!Ph``b{E6+1Xd%$@T(DxWpBc=6$_*!PXRid>YRI7s00E6c&j0`b From c4a27bff7481def9bbe84795467b66631933e05f Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 15:25:00 +0900 Subject: [PATCH 31/34] chore: Change tensorflow-intel to tensorflow-cpu --- requirements.txt | Bin 2132 -> 2128 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/requirements.txt b/requirements.txt index 4aff17fa313ce83e82736e6e7669f9712bc2a032..7389f16ad132567798044c1b21c64bd0c7ba5b1d 100644 GIT binary patch delta 22 ecmca2a6w?h9yZowh60At$rIUhH-BPFVgvwS+6U Date: Thu, 7 Sep 2023 15:32:25 +0900 Subject: [PATCH 32/34] chore: Install pytest before testing --- .github/workflows/lib-e2e-test.yml | 1 + .github/workflows/lib-unit-test.yml | 1 + 2 files changed, 2 insertions(+) diff --git a/.github/workflows/lib-e2e-test.yml b/.github/workflows/lib-e2e-test.yml index ad1c835..ccc3e3e 100644 --- a/.github/workflows/lib-e2e-test.yml +++ b/.github/workflows/lib-e2e-test.yml @@ -22,6 +22,7 @@ jobs: - name: Install dependencies run: | pip install --upgrade pip + pip install pytest pip install -r requirements.txt - name: Run e2e tests diff --git a/.github/workflows/lib-unit-test.yml b/.github/workflows/lib-unit-test.yml index 71480cc..9771104 100644 --- a/.github/workflows/lib-unit-test.yml +++ b/.github/workflows/lib-unit-test.yml @@ -22,6 +22,7 @@ jobs: - name: Install dependencies run: | pip install --upgrade pip + pip install pytest pip install -r requirements.txt - name: Run unit tests From 030b7cebb0a7ee16bcd5b2f11ef9e4b711958603 Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 15:51:19 +0900 Subject: [PATCH 33/34] chore: Setup library informations in setup.py --- setup.py | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) create mode 100644 setup.py diff --git a/setup.py b/setup.py new file mode 100644 index 0000000..5e0bd35 --- /dev/null +++ b/setup.py @@ -0,0 +1,20 @@ +from setuptools import setup, find_packages + +with open('requirements.txt') as f: + required = f.read().splitlines() + +setup( + name="face_tagger", + version="1.0.0", + description="Python library designed to classify photos containing specific individuals from a collection of " + "images.", + author="Sohn YoungJin", + author_email="sonkim1001@naver.com", + packages=find_packages(), + install_requires=required, + classifiers=[ + "Programming Language :: Python :: 3.11", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + ], +) From b377268d3d4aebf8ccb12fe05e0e78c26e21a6ea Mon Sep 17 00:00:00 2001 From: Sohn Young Jin Date: Thu, 7 Sep 2023 16:07:11 +0900 Subject: [PATCH 34/34] Release preparation for Face Tagger v1.0.0 --- pyproject.toml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index a27f772..28991c2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "hatchling.build" [project] name = "face_tagger" -version = "0.0.6" +version = "1.0.0" authors = [ { name="Bae SungJoon", email="clcc001@naver.com" }, { name="Yoon JongBeom", email="home99032@naver.com" }, @@ -13,7 +13,7 @@ authors = [ ] description = "A library for face recognition in multiple images and classification of photos containing each individual." readme = "README.md" -requires-python = ">=3.7" +requires-python = ">=3.11" classifiers = [ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License",

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