Initial commit

detecteur.py

@@ -0,0 +1,59 @@
+import os
+import sys
+import time
+import numpy as np
+import cv2
+
+cap = cv2.VideoCapture(0)
+# cap = cv2.VideoCapture("chien.mp4")
+
+kernel_blur = 5
+seuil = 15
+surface = 1000
+
+ret, originale = cap.read()
+originale = cv2.cvtColor(originale, cv2.COLOR_BGR2GRAY)
+originale = cv2.GaussianBlur(originale, (kernel_blur, kernel_blur), 0)
+
+kernel_dilate = np.ones((5, 5), np.uint8)
+
+while True:
+    ret, frame = cap.read()
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    gray = cv2.GaussianBlur(gray, (kernel_blur, kernel_blur), 0)
+    mask = cv2.absdiff(originale, gray)
+    mask = cv2.threshold(mask, seuil, 255, cv2.THRESH_BINARY)[1]
+    mask = cv2.dilate(mask, kernel_dilate, iterations=3)
+    contours, nada = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    frame_contour = frame.copy()
+    for c in contours:
+        cv2.drawContours(frame_contour, [c], 0, (0, 255, 0), 5)
+        if cv2.contourArea(c) < surface:
+            continue
+        x, y, w, h = cv2.boundingRect(c)
+        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
+    originale = gray
+    cv2.putText(frame, "[o|l]seuil: {:d}  [p|m]blur: {:d}  [i|k]surface: {:d}".format(seuil, kernel_blur, surface), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0, 255, 255), 2)
+    # cv2.imshow("frame", frame)
+    cv2.imshow("contour", frame_contour)
+    # cv2.imshow("mask", mask)
+    intrus = 0
+    key = cv2.waitKey(30) & 0xFF
+
+    if key == ord('q'):
+        break
+    if key == ord('p'):
+        kernel_blur = min(43, kernel_blur + 2)
+    if key == ord('m'):
+        kernel_blur = max(1, kernel_blur - 2)
+    if key == ord('i'):
+        surface += 1000
+    if key == ord('k'):
+        surface = max(1000, surface - 1000)
+    if key == ord('o'):
+        seuil = min(255, seuil + 1)
+    if key == ord('l'):
+        seuil = max(1, seuil - 1)
+
+cap.release()
+cv2.destroyAllWindows()