Initial commit

OpenCV/tutoriel13/README.md

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+# Tutoriel OpenCV
+## Détection d'objet par soustraction
+
+La vidéo du tutoriel est à l'adresse:
+https://www.youtube.com/watch?v=pkzT9MlICPE
+

OpenCV/tutoriel13/calcul_mask.py

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+import cv2
+import numpy as np
+import common
+
+video='autoroute.mp4'
+image_fond="img-0.png"
+color_infos=(0, 0, 255)
+
+nbr_old=0
+vehicule=0
+seuil=10
+
+fond=common.moyenne_image(video, 100)
+
+cv2.imshow('fond', fond.astype(np.uint8))
+cap=cv2.VideoCapture(video)
+
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    mask=common.calcul_mask(frame, fond, seuil)
+    elements=cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
+    nbr=0
+    for e in elements:
+        ((x, y), rayon)=cv2.minEnclosingCircle(e)
+        if rayon>20:
+            cv2.circle(frame, (int(x), int(y)), 5, color_infos, 10)
+            nbr+=1
+    if nbr>nbr_old:
+        vehicule+=1
+    nbr_old=nbr
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}  Seuil: {:d}".format(fps, seuil), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color_infos, 1)
+    cv2.imshow('video', frame)
+    cv2.imshow('mask', mask)
+    key=cv2.waitKey(1)&0xFF
+    if key==ord('q'):
+        break
+    if key==ord('p'):
+        seuil+=1
+    if key==ord('m'):
+        seuil-=1
+    if key==ord('a'):
+        for cpt in range(20):
+            ret, frame=cap.read()
+
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel13/common.py

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+import cv2
+import numpy as np
+
+def moyenne_image(video, nbr):
+    cap=cv2.VideoCapture(video)
+    tab_image=[]
+    for f in range(nbr):
+        ret, frame=cap.read()
+        if ret is False:
+            break
+        image=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        tab_image.append(image)
+    tab_image=np.array(tab_image)
+    cap.release()
+    return np.mean(tab_image, axis=0)
+
+def calcul_mask(image, fond, seuil):
+    image=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    height, width=image.shape
+    mask=np.zeros([height, width], np.uint8)
+    image=image.astype(np.int32)
+    for y in range(height):
+        for x in range(width):
+            if abs(fond[y][x]-image[y][x])>seuil:
+                mask[y][x]=255
+    kernel=np.ones((5, 5), np.uint8)
+    mask=cv2.erode(mask, kernel, iterations=1)
+    mask=cv2.dilate(mask, kernel, iterations=3)
+    return mask

OpenCV/tutoriel13/compte.py

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+import cv2
+import numpy as np
+import common
+
+color_infos=(0, 0, 255)
+xmin=90
+xmax=510
+ymin=315
+ymax=360
+video='autoroute.mp4'
+
+nbr_old=0
+vehicule=0
+seuil=10
+
+fond=common.moyenne_image(video, 500)
+fond=fond[ymin:ymax, xmin:xmax]
+cv2.imshow('fond', fond.astype(np.uint8))
+fond=fond.astype(np.int32)
+cap=cv2.VideoCapture(video)
+
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    mask=common.calcul_mask(frame[ymin:ymax, xmin:xmax], fond, seuil)
+    elements=cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
+    nbr=0
+    for e in elements:
+        ((x, y), rayon)=cv2.minEnclosingCircle(e)
+        if rayon>20:
+            cv2.circle(frame, (int(x)+xmin, int(y)+ymin), 5, color_infos, 10)
+            nbr+=1
+    if nbr>nbr_old:
+        vehicule+=1
+    nbr_old=nbr
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}  Seuil: {:d}".format(fps, seuil), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color_infos, 1)
+    cv2.rectangle(frame, (xmin, ymin), (xmax+120, ymax), (255, 0, 0), 5)
+    cv2.rectangle(frame, (xmax, ymin), (xmax+120, ymax), (255, 0, 0), cv2.FILLED)
+    cv2.putText(frame, "{:04d}".format(vehicule), (xmax+10, ymin+35), cv2.FONT_HERSHEY_COMPLEX_SMALL, 2, (255, 255, 255), 2)
+    cv2.imshow('video', frame)
+    cv2.imshow('mask', mask)
+    key=cv2.waitKey(1)&0xFF
+    if key==ord('q'):
+        break
+    if key==ord('p'):
+        seuil+=1
+    if key==ord('m'):
+        seuil-=1
+
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel13/compte_v2.py

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+import cv2
+import numpy as np
+import common
+
+color_infos=(0, 0, 255)
+
+ymin=315
+ymax=360
+
+xmin1=110
+xmax1=190
+
+xmin2=250
+xmax2=330
+
+xmin3=380
+xmax3=460
+
+video='autoroute.mp4'
+
+vehicule1=0
+vehicule2=0
+vehicule3=0
+seuil=10
+seuil2=100
+
+fond=common.moyenne_image(video, 500)
+fond=fond[ymin:ymax, xmin1:xmax3]
+cv2.imshow('fond', fond.astype(np.uint8))
+fond=fond.astype(np.int32)
+cap=cv2.VideoCapture(video)
+
+def calcul_mean(image):
+    height, width=image.shape
+    s=0
+    for y in range(height):
+        for x in range(width):
+            s+=image[y][x]
+    return s/(height*width)
+
+old_1=0
+old_2=0
+old_3=0
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    mask=common.calcul_mask(frame[ymin:ymax, xmin1:xmax3], fond, seuil)
+
+    if calcul_mean(mask[0:ymax-ymin, 0:xmax1-xmin1])> seuil2:
+        if old_1==0:
+            vehicule1+=1
+            old_1=1
+    else:
+        old_1=0
+
+    if calcul_mean(mask[0:ymax-ymin, xmin2-xmin1:xmax2-xmin1])> seuil2:
+        if old_2==0:
+            vehicule2+=1
+            old_2=1
+    else:
+        old_2=0
+
+    if calcul_mean(mask[0:ymax-ymin, xmin3-xmin1:xmax3-xmin1])> seuil2:
+        if old_3==0:
+            vehicule3+=1
+            old_3=1
+    else:
+        old_3=0
+
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}  Seuil: {:d}".format(fps, seuil), (10, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, color_infos, 1)
+    cv2.putText(frame, "{:04d} {:04d} {:04d}".format(vehicule1, vehicule2, vehicule3), (xmin1, ymin-10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 2, (255, 255, 255), 2)
+    cv2.rectangle(frame, (xmin1, ymin), (xmax1, ymax), (0, 0, 255) if old_1 else (255, 0, 0), 3)
+    cv2.rectangle(frame, (xmin2, ymin), (xmax2, ymax), (0, 0, 255) if old_2 else (255, 0, 0), 3)
+    cv2.rectangle(frame, (xmin3, ymin), (xmax3, ymax), (0, 0, 255) if old_3 else (255, 0, 0), 3)
+    cv2.imshow('video', frame)
+    cv2.imshow('mask', mask)
+    key=cv2.waitKey(1)&0xFF
+    if key==ord('q'):
+        break
+    if key==ord('p'):
+        seuil+=1
+    if key==ord('m'):
+        seuil-=1
+
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel13/moyenne.py

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+import cv2
+import numpy as np
+import common
+
+image=common.moyenne_image('autoroute.mp4', 100)
+cv2.imshow('fond', image.astype(np.uint8))
+cv2.waitKey()
+cap.release()
+cv2.destroyAllWindows()