Work on eval_single_similarity.py

Signed-off-by: Martin <[email protected]>

.gitignore

@@ -171,6 +171,7 @@ cython_debug/
 *.pt
 *.pth
 *.weights
+*.pickle
 
 # automatically generated files for docs
 /docs/dgs_autosummary

configs/DGS/eval_sim_indep.yaml

@@ -19,19 +19,22 @@ test:
 dl_rcnn:
     module_name: "KeypointRCNNImageBackbone"
     dataset_path: "./data/"
-    # data_path:  # will be set in python script
     base_path: "./data/PoseTrack21/images/val/"
     batch_size: 8
     threshold: 0.75
     return_lists: true
+    crop_size: !!python/tuple [256, 192]
+    crop_mode: "zero-pad"
+    # data_path:  # will be set in python script
 
 dl_gt:
     module_name: "PoseTrack21_Image"
     dataset_path: "./data/PoseTrack21/"
-    # data_path: # will be set in python script
+    crops_folder: "./data/PoseTrack21/crops/256x192/val/"
     base_path: "./data/PoseTrack21/posetrack_data/val/"
     batch_size: 8
     return_lists: true
+    # data_path: # will be set in python script
 
 # ####### #
 # MODULES #

scripts/own/eval_single_similarity.py

@@ -17,22 +17,24 @@
 from dgs.models.loader import module_loader
 from dgs.utils.config import load_config
 from dgs.utils.torchtools import close_all_layers, memory_analysis
+from dgs.utils.types import Config
 from dgs.utils.utils import HidePrint
 
 CONFIG_FILE = "./configs/DGS/eval_sim_indep.yaml"
 
 
 @memory_analysis
 @torch.no_grad()
-def run(dl_key: str, paths: list[str]) -> None:
+def run(config: Config, dl_key: str, paths: list[str]) -> None:
     """Main function to run the code."""
-    # get sub folders or files and analyse them one-by-one
-    for sub_datapath in tqdm(paths, desc="ds_sub_dir"):
+    # IoU, OKS, and visual similarity
+    for dgs_key in tqdm(["dgs_box", "dgs_pose", "dgs_vis_3", "dgs_vis_2", "dgs_vis_3"], desc="similarities"):
+        # for dgs_key in tqdm(["dgs_vis_3", "dgs_vis_2", "dgs_vis_3"], desc="similarities"):
 
-        config[dl_key]["data_path"] = sub_datapath
+        # get sub folders or files and analyse them one-by-one
+        for sub_datapath in tqdm(paths, desc="ds_sub_dir"):
 
-        # IoU, OKS, and visual similarity
-        for dgs_key in tqdm(["dgs_box", "dgs_pose", "dgs_vis_3", "dgs_vis_2", "dgs_vis_3"], desc="similarities"):
+            config[dl_key]["data_path"] = sub_datapath
 
             # make sure to have a unique log dir every time
             orig_log_dir = config["log_dir"]
@@ -57,15 +59,14 @@ def run(dl_key: str, paths: list[str]) -> None:
 if __name__ == "__main__":
     print(f"Cuda available: {torch.cuda.is_available()}")
 
-    print(f"Loading configuration: {CONFIG_FILE}")
-    config = load_config(CONFIG_FILE)
-
     print("Evaluating on the PT21 ground-truth evaluation dataset")
-    base_path = config["dl_gt"]["base_path"]
+    cfg = load_config(CONFIG_FILE)
+    base_path = cfg["dl_gt"]["base_path"]
     data_paths = [f.path for f in os.scandir(base_path) if f.is_file()]
-    run(dl_key="dl_gt", paths=data_paths)
+    run(config=cfg, dl_key="dl_gt", paths=data_paths)
 
     print("Evaluating on the PT21 eval-dataset using KeypointRCNN as prediction backbone")
-    base_path = config["dl_rcnn"]["base_path"]
+    cfg = load_config(CONFIG_FILE)
+    base_path = cfg["dl_rcnn"]["base_path"]
     data_paths = [f.path for f in os.scandir(base_path) if f.is_dir()]
-    run(dl_key="dl_rcnn", paths=data_paths)
+    run(config=cfg, dl_key="dl_rcnn", paths=data_paths)