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level.py
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level.py
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import imutils
import numpy as np
import cv2 as cv
import math
import time
import copy
import glob
from cam import *
from dictionary import search_dictionary, search_backup_dictionary, sort_words_20x
from recognition import can_have_three_letters
template_files = glob.glob("letters/*.PNG")
letter_template_pairs = []
DEBUG_VIDEO = False
circle_mask = cv.imread('mask_2.png',0)
def get_template(filename): #load the template image and crop it.
img = cv.imread(filename, 0)
ret,img = cv.threshold(img,200,255,cv.THRESH_BINARY)
inverse = cv.bitwise_not(img)
cnts, _ = cv.findContours(inverse, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
cnts = [c for c in cnts if cv.boundingRect(c)[3] > 10]
contour = cnts[0]
bx, by, bw, bh = cv.boundingRect(contour)
img = img[by:by+bh, bx:bx+bw]
resized = cv.resize(img, (20, 25), interpolation = cv.INTER_AREA)
return resized
for t in template_files:
letter = t.split("letters/")[1][0]
template = get_template(t)
letter_template_pairs.append((letter, template))
def how_similar(img1, img2):
img = cv.bitwise_xor(img1, img2)
m = cv.mean(img)[0]
return 255-m
last_circle_coord = None
def get_circle_coord(img):
global last_circle_coord
circles = cv.HoughCircles(img,cv.HOUGH_GRADIENT,1,20,
param1=50,param2=30,minRadius=55,maxRadius=70) #param1 = 100
try:
circles = np.uint16(np.around(circles))
except:
return last_circle_coord
for i in circles[0,:]:
last_circle_coord = i
return i
def get_center():
x, y, r = last_circle_coord
return (x,y)
def flush_camera():
for i in range(20):
_ = get_gray()
def get_all_combos(data):
if len(data) == 0:
return []
if len(data) == 1:
return [[x] for x in data[0]]
combos = get_all_combos(data[1:])
new_combos = []
for letter in data[0]:
new_combos = new_combos + [[letter]+combo for combo in combos]
return new_combos
class Level():
letters = []
letters_scores = []
attempts = 0
center = None
relax_constant = 10
tried_moves = []
def equals(self, level):
a = [x for x in self.letters if x not in level.letters]
return len(a) < 2
def check_for_max_letter_words(self):
all_availables = []
#[[A:200, B:199], [A:200, B:199]]
for score_chart in self.letters_scores:
best_score = score_chart[0][0]
availables = [x[1] for x in score_chart if x[0] > best_score-self.relax_constant]
all_availables.append(availables)
combos = get_all_combos(all_availables)
other_valid_letters = []
for potential in combos:
trial_words = search_dictionary(potential)
if len(trial_words) > 0 and len(trial_words[-1]) == len(self.letters):
print("max letter words", trial_words)
trial_words = sort_words_20x(trial_words, len(self.letters))
return [self.word_to_locations(word, potential) for word in trial_words]
def word_to_locations(self, word, letters):
word_moves = []
locations = self.locations[:]
letters = letters[:]
for i, letter in enumerate(word):
for l, location in zip(letters, locations):
if l == letter:
word_moves.append(location)
locations.remove(location)
letters.remove(l)
break
return word_moves
def get_moves(self):
print("attempts", self.attempts)
three_letters = can_have_three_letters()
letters = self.letters
if self.attempts == 0:
moves = self.check_for_max_letter_words()
if moves:
return moves
else:
self.attempts += 1
words = search_dictionary(letters, three_letters)
if self.attempts == 1:
if words and len(words) > 5:
if words and len(words[-1]) != len(letters):
words += search_backup_dictionary(letters, three_letters)
words = list(set(words))
words = sort_words_20x(words, len(letters))
print(words)
moves = [self.word_to_locations(word, self.letters) for word in words]
return moves
else:
self.attempts += 1
if self.attempts == 2:
if words:
words = sort_words_20x(words, len(letters))
print(words)
moves = [self.word_to_locations(word, self.letters) for word in words]
self.tried_moves += moves
return moves
else:
self.attempts += 1
all_availables = []
#[[A:200, B:199], [A:200, B:199]]
for score_chart in self.letters_scores:
best_score = score_chart[0][0]
availables = [x[1] for x in score_chart if x[0] > best_score-self.relax_constant]
all_availables.append(availables)
combos = get_all_combos(all_availables)
other_valid_letters = []
for potential in combos:
trial_words = search_dictionary(potential, three_letters)
if len(trial_words) > 0:
other_valid_letters.append((potential, trial_words))
i = self.attempts - 3
if len(other_valid_letters) == 0:
print("all our guesses are terrible")
return None
if i > len(other_valid_letters):
print("We've tried everything", len(other_valid_letters))
return None
i = self.attempts % len(other_valid_letters)
letters, words, locations = other_valid_letters[i][0], other_valid_letters[i][1], self.locations
words = sort_words_20x(words, len(letters))
print(words)
moves = [self.word_to_locations(word, letters) for word in words]
moves = [m for m in moves if m not in self.tried_moves]
self.tried_moves += moves
if len(moves) == 0:
self.attempts += 1
return self.get_moves()
return moves
def threshold_and_crop(gray):
for i in range(20):
coord = get_circle_coord(gray)
try:
x, y, r = coord
r = r-1
crop_x, crop_y, crop_w, crop_h = x-r, y-r, r*2, r*2
gray = gray[crop_y:crop_y+crop_h, crop_x:crop_x+crop_w]
except:
print("No Circle")
show_image(gray)
return None
center, reach = crop_w // 2, crop_w // 5
center_circle = gray[center-reach:center+reach, center-reach:center+reach]
try:
gray = cv.bilateralFilter(gray,5,75,75)
except:
print("Extra Crop")
return #we've cropped away the whole image.
m = cv.mean(center_circle)[0]
m2 = cv.mean(gray)[0]
inverted = cv.bitwise_not(gray)
center_color = 255-m
ret,threshed = cv.threshold(inverted, center_color,255,cv.THRESH_TRUNC)
ret,threshed = cv.threshold(threshed,center_color*1/5,255,cv.THRESH_BINARY)
threshed2 = cv.adaptiveThreshold(gray, 255, cv.ADAPTIVE_THRESH_GAUSSIAN_C,cv.THRESH_BINARY,11,2)
show_image(threshed)
if m > m2: # flop flop threshed and threshed2
t = threshed
threshed = threshed2
threshed2 = t
mask = cv.resize(circle_mask, (r*2, r*2), interpolation = cv.INTER_AREA)
try: #apply mask
threshed = cv.bitwise_or(threshed, mask)
threshed2 = cv.bitwise_or(threshed2, mask)
except:
return None
return threshed, threshed2, crop_x, crop_y
def get_level_data(frame=None, debug=False):
if frame is None:
gray = get_gray()
else:
gray = frame
data = threshold_and_crop(gray)
if not data:
return
threshed, threshed2, crop_x, crop_y = data
inverted, inverted2 = cv.bitwise_not(threshed), cv.bitwise_not(threshed2)
letter_contours = get_letter_contours(inverted)
if len(letter_contours) < 5:
letter_contours = get_letter_contours(inverted2)
if len(letter_contours) < 5:
return None
else:
inverted = inverted2
threshed = threshed2
letters = []
letters_scores = []
locations = []
imgs = []
#TODO: Add a min threshold for the best_score so that we don't detect garbage as a letter.
for contour in letter_contours:
bx, by, bw, bh = cv.boundingRect(contour)
x, y = bx+(bw/2), by+(bh/2) #center of contour bounding box
location = (x+crop_x, y+crop_y)
cropped = threshed[by:by+bh, bx:bx+bw]
im = cv.resize(cropped, (20, 25), interpolation = cv.INTER_AREA)
scores = []
for letter, letter_template in letter_template_pairs:
if letter == "I":
if bw > 7:
score = 140
else:
score = 230
else:
score = how_similar(im, letter_template)
scores.append((score, letter))
scores.sort()
scores = scores[::-1]
if scores[0][0] < 160:
continue
letters_scores.append(scores)
locations.append(location)
letters.append(scores[0][1])
if DEBUG_VIDEO or debug:
cv.rectangle(threshed,(bx-3, by-3), (bx+bw+3, by+bh+3), 150, 2) #make sure this is at the end.
if len(letters) < 5:
return None
if debug:
cv.imshow('image', threshed)
k = cv.waitKey(0)
if DEBUG_VIDEO:
#show_image(threshed)
print(letters)
level = Level()
level.letters = letters
level.letters_scores = letters_scores
level.locations = locations
level.center = get_center()
print(letters)
return level
def get_letter_contours(inverted):
h, w = inverted.shape
all_contours, heirarchy = cv.findContours(inverted, cv.RETR_EXTERNAL, cv.CHAIN_APPROX_SIMPLE)
letter_contours = []
for contour in all_contours:
bx, by, bw, bh = cv.boundingRect(contour)
if bh < 10 or bh < 15: continue #too small
if bw > 45 or bh > 30: continue # too big
x, y = bx+(bw/2), by+(bh/2) #center of contour bounding box
dx, dy = (w/2)-x, (h/2)-y
dm = math.sqrt(dx * dx + dy * dy)
if dm > (w / 2) - 8 or dm < 35: #this filters out anything thats not on inside edge of the bounding circle. Replaces the mask
continue
letter_contours.append(contour)
return letter_contours
if __name__ == "__main__":
DEBUG_VIDEO = True
while True:
get_level_data()