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https://github.com/3x4byte/StreetsignRecognition.git
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50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import cv2
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import numpy as np
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from os import walk
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import csv
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def detect_corners(gray_image, max_corners=100, quality_level=0.14, min_distance=1):
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corners = cv2.goodFeaturesToTrack(cv2.blur(gray_image, (5,5)), maxCorners=max_corners, qualityLevel=quality_level, minDistance=min_distance)
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if corners is not None:
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corners = np.int0(corners)
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return len(corners), corners
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else:
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return 0, []
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def detect_edges(gray_image):
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edges = cv2.Canny(cv2.blur(gray_image, (5,5)), threshold1=100, threshold2=200)
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edge_count = np.count_nonzero(edges)
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return edge_count, edges
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def detect_contours(edge_image):
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contours, _ = cv2.findContours(edge_image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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contour_count = len(contours)
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return contour_count, contours
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def feature_vector(image_path):
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resultVector = {}
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img = cv2.imread(image_path)
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image_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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corners_count, _ = detect_corners(image_gray)
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edges_count, edges = detect_edges(image_gray)
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contours_count, _ = detect_contours(edges)
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resultVector["corners"] = corners_count % 100
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resultVector["edges"] = edges_count / 1000
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resultVector["contours"] = contours_count * 0.1
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return resultVector
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filenames = next(walk("images"), (None, None, []))[2] # [] if no file
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with open('dict.csv', 'w') as csv_file:
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writer = csv.DictWriter(csv_file, fieldnames=['corners', 'edges', 'contours'])
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writer.writeheader()
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for filename in filenames:
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result = feature_vector(f'images/{filename}')
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writer.writerow(result) |