Appended contrast function

Contrast function https://www.w3.org/TR/WCAG21/
---------

Co-authored-by: Иван Горбунов <muervos@muervos.muervos>

requirements.txt

@@ -6,8 +6,9 @@ pytesseract==0.3.10
 pytest==7.2.2
 python_Levenshtein==0.20.9
 colorama==0.4.6
+matplotlib==3.9.4
 opencv-python==4.10.0.84
 mss==9.0.1
 qat==1.1.2
 pyyaml==5.3.1
-pyscreeze==0.1.21
+pyscreeze==1.0.1

src/pygats/boxes.py

@@ -0,0 +1,20 @@
+# pytesseract boxes
+import cv2 as cv
+import pytesseract
+"https://programmersought.com/article/896710504463/"
+
+img = cv.imread("./src/pygats/test1.png")
+
+img = cv.cvtColor(img, cv.COLOR_BGR2RGB)
+
+hImg, wImg, _ = img.shape
+
+boxes = pytesseract.image_to_boxes(img)
+for b in boxes.splitlines():
+    b = b.split(' ')
+    print(b)
+    x, y, w, h = int(b[1]), int(b[2]), int(b[3]), int(b[4])
+    cv.rectangle(img, (x, hImg - y), (w, hImg - h), (0, 0, 255), 2)
+
+cv.imshow("img", img)
+cv.waitKey(0)

src/pygats/search.py

@@ -0,0 +1,69 @@
+from pathlib import Path
+import cv2
+import pytesseract
+from matplotlib import pyplot as plt
+from PIL import Image
+import src.pygats.recog as rec
+import src.pygats.pygats as pyg
+from src.pygats.formatters import MarkdownFormatter as MD
+
+ctx = pyg.Context(MD())
+
+
+def find_text():
+    img = cv2.imread("./src/pygats/test1.png")
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+    ret, thresh1 = cv2.threshold(gray, 0, 255, cv2.THRESH_OTSU | cv2.THRESH_BINARY_INV)
+    rect_kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (20, 25))
+    dilation = cv2.dilate(thresh1, rect_kernel, iterations=1)
+    edges = cv2.Canny(gray, 100, 200)
+    plt.imshow(edges, cmap='gray')
+    plt.show()
+    contours, hierarchy = cv2.findContours(
+        dilation, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE
+    )
+    sift = cv2.SIFT_create()
+    keypoints, descriptors = sift.detectAndCompute(thresh1, None)
+    image_with_sift = cv2.drawKeypoints(thresh1, keypoints, None)
+    plt.imshow(cv2.cvtColor(image_with_sift, cv2.COLOR_BGR2RGB))
+    plt.title('SIFT Features')
+    plt.show()
+    print(f"Найдено контуров: {len(contours)}")
+    im2 = img.copy()
+    cv2.imwrite("./src/pygats/after.png", im2)
+    search_folder = Path('./src/pygats/search_folder')
+    search_folder.mkdir(parents=True, exist_ok=True)
+    with open("./tests/find/result.txt", "w+") as file:
+        for cnt in contours:
+            x, y, w, h = cv2.boundingRect(cnt)
+            cv2.rectangle(im2, (x, y), (x + w, y + h), (0, 255, 0), 2)
+            cropped = im2[y:y + h, x:x + w]
+            text = pytesseract.image_to_string(cropped, "rus")
+            print(f"Распознанный текст: '{text}'")
+            file.write(text)
+            cv2.imwrite(f"./src/pygats/search_folder/{cnt}.png", cropped)
+        file.close()
+
+
+def pygats_search():
+    file = open("tests/find/words.ru.txt")
+    texts = []
+    good_result = 0
+    failed_count = 0
+    text_count = 0
+    lines = file.readlines()
+    for line in lines:
+        if not line.strip():
+            continue
+        text_count += 1
+        try:
+            text = rec.SearchedText(line.strip(), "rus", None)
+            texts.append(text)
+            img = Image.open("./src/pygats/test1.png")
+            rec.check_text(ctx, img, text)
+            good_result += 1
+        except pyg.TestException:
+            failed_count += 1
+        if text_count >= 9:
+            break
+    print("успешно распознанных слов: ", good_result, "\n", "не распознанных слов: ", failed_count)

tests/find/gen.py

@@ -1,7 +1,7 @@
 from pathlib import Path
 import time
 from PIL import Image, ImageDraw, ImageFont
-
+from pygats.search import pygats_search
 
 def crop_image(img, w, h):
     img_crop = img.crop((0, 0, w, h))
@@ -11,7 +11,7 @@ def crop_image(img, w, h):
 def wrapper():
     folder_result = Path(f'tests/find/result.txt')
     start = time.time()
-    #gen("white", 350, 350, 'TimesNewRoman', 32, "File")
+    pygats_search()
     seconds = int(time.time() - start)
     seconds = seconds % (24 * 3600)
     hours = seconds // 3600
@@ -65,4 +65,6 @@ def color_shade_gen(step: tuple = (1, 1, 1), size: tuple = (1920, 1080)):
         new_image_data = [rgb] * (size[0] * size[1])
         new_img = Image.new('RGB', size)
         new_img.putdata(new_image_data)
-        new_img.save(f"{folder_path}/color:{rgb}.png", 'PNG')
+        new_img.save(f"{folder_path}/color:{rgb}.png", 'PNG')
+
+wrapper()