Python - OpenCV+MatplotLib

Python/OpenCV/draw_pytesseract_boxes.py

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+from pytesseract import Output
+import pytesseract
+import cv2
+ 
+image = cv2.imread("my_image.jpg")
+
+#swap color channel ordering from BGR (OpenCV’s default) to RGB (compatible with Tesseract and pytesseract).
+# By default OpenCV stores images in BGR format and since pytesseract assumes RGB format,
+# we need to convert from BGR to RGB format/mode:
+rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+ 
+pytesseract.pytesseract.tesseract_cmd = r'C:\mypath\tesseract.exe'
+custom_config = r'-c tessedit_char_whitelist=0123456789 --psm 6'
+results = pytesseract.image_to_data(rgb, output_type=Output.DICT,lang='eng',config=custom_config)
+boxresults = pytesseract.image_to_boxes(rgb,output_type=Output.DICT,lang='eng',config=custom_config)
+print(results)
+print(boxresults)
+
+for i in range(0, len(results["text"])):
+    # extract the bounding box coordinates of the text region from the current result
+    tmp_tl_x = results["left"][i]
+    tmp_tl_y = results["top"][i]
+    tmp_br_x = tmp_tl_x + results["width"][i]
+    tmp_br_y = tmp_tl_y + results["height"][i] 
+    tmp_level = results["level"][i]
+    conf = results["conf"][i]
+    text = results["text"][i]
+    
+    if(tmp_level == 5):
+        cv2.putText(image, text, (tmp_tl_x, tmp_tl_y - 10), cv2.FONT_HERSHEY_SIMPLEX,0.5, (0, 0, 255), 1)
+        cv2.rectangle(image, (tmp_tl_x, tmp_tl_y), (tmp_br_x, tmp_br_y), (0, 0, 255), 1)
+        
+for j in range(0,len(boxresults["left"])):
+    left = boxresults["left"][j]
+    bottom = boxresults["bottom"][j]
+    right = boxresults["right"][j]
+    top = boxresults["top"][j] 
+    cv2.rectangle(image, (left, top), (right, bottom), (255, 0, 0), 1)
+       
+    
+cv2.imshow("image",image)
+cv2.waitKey(0)

Python/OpenCV/find_rectangular_shapes.py

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+import cv2
+
+# Load iamge, grayscale, adaptive threshold
+image = cv2.imread('1.png')
+result = image.copy()
+gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
+thresh = cv2.adaptiveThreshold(gray,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV,51,9)
+
+# Fill rectangular contours
+cnts = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+cnts = cnts[0] if len(cnts) == 2 else cnts[1]
+for c in cnts:
+    cv2.drawContours(thresh, [c], -1, (255,255,255), -1)
+
+# Morph open
+kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (9,9))
+opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=4)
+
+# Draw rectangles
+cnts = cv2.findContours(opening, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+cnts = cnts[0] if len(cnts) == 2 else cnts[1]
+for c in cnts:
+    x,y,w,h = cv2.boundingRect(c)
+    cv2.rectangle(image, (x, y), (x + w, y + h), (36,255,12), 3)
+
+cv2.imshow('thresh', thresh)
+cv2.imshow('opening', opening)
+cv2.imshow('image', image)
+cv2.waitKey()

Python/matplotlib/display_image_as_grayscale.py

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+import numpy as np
+import matplotlib.pyplot as plt
+from PIL import Image
+
+fname = 'image.png'
+image = Image.open(fname).convert("L")
+arr = np.asarray(image)
+plt.imshow(arr, cmap='gray', vmin=0, vmax=255)
+plt.show()
+
+# If you want to display the inverse grayscale, switch the cmap to cmap='gray_r'

Python/matplotlib/display_multiple_images_in_grid.py

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+import cv2
+import glob
+import matplotlib.pyplot as plt
+
+path="data/*.jpg"
+
+images=[cv2.imread(image) for image in glob.glob(path)]
+fig=plt.figure()
+for i in range(len(images)):
+    plt.subplot(5,5,i+1)
+    plt.imshow(images[i])
+plt.show()