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June 20, 2019 20:56
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| import cv2 as cv | |
| import math | |
| import matplotlib.pyplot as plt | |
| import matplotlib.image as mpimg | |
| from detectors.color_detector import ColorDetector | |
| from processes.blurs import Blurs | |
| import numpy as np | |
| # load video | |
| cap = cv.VideoCapture('testvideo.mp4') | |
| # cap = cv.VideoCapture(0) | |
| blurs = Blurs() | |
| colorDetector = ColorDetector(lhsv = np.array([30, 60, 0]), uhsv = np.array([179, 255, 255])) | |
| # colorDetector.enable_trackbars() | |
| # Get shape of frame | |
| width = cap.get(3) | |
| height = cap.get(4) | |
| # Percent of frame cropped for height and width | |
| crop_height = 0.85 | |
| crop_width = 0 | |
| # 4 Points that define the point of intrest for the frame. The side walk should be near the center | |
| # This array defines a trapazoid. | |
| region_of_interest_vertices = [ | |
| (0, height * crop_height), | |
| (width * crop_width, height * (1 - crop_height)), | |
| (width * (1 - crop_width), height * (1 - crop_height)), | |
| (width, height * crop_height), | |
| ] | |
| # Draw lines given a frame and an array of line start/end coordinates | |
| def draw_lines(img, lines, color=[255, 0, 0], thickness=3): | |
| line_img = np.zeros( | |
| ( | |
| img.shape[0], | |
| img.shape[1], | |
| 3 | |
| ), | |
| dtype=np.uint8 | |
| ) | |
| img = np.copy(img) | |
| if lines is None: | |
| return | |
| for line in lines: | |
| for x1, y1, x2, y2 in line: | |
| cv.line(line_img, (int(x1), int(y1)), (int(x2), int(y2)), color, thickness) | |
| img = cv.addWeighted(img, 0.8, line_img, 1.0, 0.0) | |
| return img | |
| # Crop frame | |
| def crop(img, vertices): | |
| # Define a blank matrix that matches the image height/width. | |
| mask = np.zeros_like(img) | |
| #defining a 3 channel or 1 channel color to fill the mask with depending on the input image | |
| if len(img.shape) > 2: | |
| channel_count = img.shape[2] # i.e. 3 or 4 depending on your image | |
| ignore_mask_color = (255,) * channel_count | |
| else: | |
| ignore_mask_color = 255 | |
| #filling pixels inside the polygon defined by "vertices" with the fill color | |
| cv.fillPoly(mask, vertices, ignore_mask_color) | |
| #returning the image only where mask pixels are nonzero | |
| masked_image = cv.bitwise_and(img, mask) | |
| return masked_image | |
| # Main processing | |
| while True: | |
| _, init_frame = cap.read() | |
| frame = blurs.average_blur(init_frame, 30) | |
| cropped_frame = crop( | |
| init_frame, | |
| np.array([region_of_interest_vertices], np.int32), | |
| ) | |
| mask = colorDetector.get_mask(cropped_frame) | |
| mask = cv.bitwise_not(mask) | |
| colored_frame = cv.bitwise_and(cropped_frame, cropped_frame, mask = mask) | |
| edges = cv.Canny(mask, 200, 200) | |
| cropped_edges = crop( | |
| edges, | |
| np.array([region_of_interest_vertices], np.int32), | |
| ) | |
| lines = cv.HoughLinesP( | |
| cropped_edges, | |
| rho=6, | |
| theta=np.pi / 60, | |
| threshold=160, | |
| lines=np.array([]), | |
| minLineLength=100, | |
| maxLineGap=25 | |
| ) | |
| # If no lines are detected in the frame | |
| if np.shape(lines) != (): line_image = draw_lines(init_frame, lines) | |
| else: line_image = init_frame | |
| mask = cv.cvtColor(mask, cv.COLOR_GRAY2BGR) | |
| cropped_edges = cv.cvtColor(cropped_edges, cv.COLOR_GRAY2BGR) | |
| #out = np.concatenate((line_image, line_image2), axis = 1) | |
| cv.imshow("out", line_image) | |
| key = cv.waitKey(1) | |
| if key == 27: | |
| break | |
| cap.release() | |
| cv.destroyAllWindows() |
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