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"
])