added FV generator for edges,corners,counters

edges-corners-counters.py

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