def original_demo(image): orig = image.copy() # <---- RESIZING -----> # image, ratio = functions.standard_resize(image, new_width=100.0) # <---- RESIZING -----> # processed = functions.colorOps(image) points = functions.contour_method(processed) detection = cv2.drawContours(image.copy(), [points], -1, (0, 255, 0), 2) final = functions.finalize(orig, points, ratio) images = [orig, detection, final] functions.plot_images(images)
def text_region_method2(image): orig = image.copy() edged = functions.text_edging(orig.copy()) kernel = np.ones((9, 9), np.uint8) # original 9x9 dilated = cv2.dilate( edged, kernel, iterations=7) # original was 5 iterations. This works a little better? points = functions.minRectMethod(dilated) detection = cv2.drawContours(image.copy(), [points], -1, (0, 255, 0), 2) final = functions.finalize(orig.copy(), points) functions.plot_images( [orig, edged, dilated, detection, final], ["Original", "Edged", "Dilated", "Detection", "Final"])
def occlusion_demo(image): orig = image.copy() # <---- RESIZING -----> # image, ratio = functions.standard_resize(image, new_width=100.0) # <---- RESIZING -----> # edged = functions.colorOps(image) processed = functions.closed_inversion(edged) points = functions.minRectMethod(processed) imutils.negative_coords(points, processed.shape[1], processed.shape[0]) # points = functions.minRectMethod(edged) detection = cv2.drawContours(image.copy(), [points], -1, (0, 255, 0), 2) final = functions.finalize(orig.copy(), points, ratio) # cv2.imwrite('processed/final.jpg', final) functions.plot_images([orig, edged, processed, detection, final], [ "Original", "Edge Detection", "Morpohological Operations", "Contour Finding", "Perspective Transform" ])