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OpenCV/tutoriel3/README.md

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+# Tutoriel OpenCV
+## Détection d'objet avec la fonction detectMultiScale
+
+Si vous souhaitez me soutenir: <https://fr.tipeee.com/l42-project>
+
+Pour utiliser OpenCV, il suffit d'installer le package suivant:
+
+`# pip install opencv-python`
+
+Je vous conseille aussi d'installer:
+
+`# pip install opencv-contrib-python`
+
+La vidéo du tutoriel est à l'adresse:
+https://www.youtube.com/watch?v=-3xbAkCWJCc
+
+

OpenCV/tutoriel3/body_camera.py

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+import cv2
+
+face_cascade=cv2.CascadeClassifier("./haarcascade_fullbody.xml")
+cap=cv2.VideoCapture(0)
+
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    face=face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=3)
+    for x, y, w, h in face:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+    if cv2.waitKey(1)&0xFF==ord('q'):
+        break
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+    cv2.imshow('video', frame)
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel3/cars.mp4

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+oid sha256:57b6dc1aa21d50310d46a63a8cbd4ac47843c9195fac1be8259d6e1e604c4372
+size 81001739

OpenCV/tutoriel3/cars.py

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+import cv2
+import numpy as np
+
+object_cascade=cv2.CascadeClassifier("./cars.xml")
+cap=cv2.VideoCapture('cars.mp4')
+
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    object=object_cascade.detectMultiScale(gray, scaleFactor=1.10, minNeighbors=3)
+    for x, y, w, h in object:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+    cv2.imshow('video', frame)
+    if cv2.waitKey(1)&0xFF==ord('q'):
+        break
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel3/visage_camera.py

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+import cv2
+
+face_cascade=cv2.CascadeClassifier("./haarcascade_frontalface_alt2.xml")
+cap=cv2.VideoCapture(0)
+
+while True:
+    ret, frame=cap.read()
+    tickmark=cv2.getTickCount()
+    gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    face=face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=3)
+    for x, y, w, h in face:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+    if cv2.waitKey(1)&0xFF==ord('q'):
+        break
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+    cv2.imshow('video', frame)
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel3/visage_camera_raspberry.py

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+import numpy as np
+import cv2
+import picamera
+import picamera.array
+
+WIDTH=640
+HEIGHT=480
+
+face_cascade=cv2.CascadeClassifier("./haarcascade_frontalface_alt2.xml")
+with picamera.PiCamera() as camera:
+    with picamera.array.PiRGBArray(camera) as stream:
+        camera.resolution=(WIDTH, HEIGHT)
+        while True:
+            camera.capture(stream, 'bgr', use_video_port=True)
+            tickmark=cv2.getTickCount()
+            gray=cv2.cvtColor(stream.array, cv2.COLOR_BGR2GRAY)
+            face=face_cascade.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=4)
+            for x, y, w, h in face:
+                cv2.rectangle(stream.array, (x, y), (x+w, y+h), (255, 0, 0), 2)
+            if cv2.waitKey(1)&0xFF==ord('q'):
+                break
+            fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+            cv2.putText(stream.array, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+            cv2.imshow('video', stream.array)
+            stream.seek(0)
+            stream.truncate()
+cv2.destroyAllWindows()

OpenCV/tutoriel3/visage_camera_v2.py

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+import cv2
+import operator
+
+face_cascade=cv2.CascadeClassifier("./haarcascade_frontalface_alt2.xml")
+profile_cascade=cv2.CascadeClassifier("./haarcascade_profileface.xml")
+cap=cv2.VideoCapture(0)
+width=int(cap.get(3))
+marge=70
+
+while True:
+    ret, frame=cap.read()
+    tab_face=[]
+    tickmark=cv2.getTickCount()
+    gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    face=face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=4, minSize=(5, 5))
+    for x, y, w, h in face:
+        tab_face.append([x, y, x+w, y+h])
+    face=profile_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=4)
+    for x, y, w, h in face:
+        tab_face.append([x, y, x+w, y+h])
+    gray2=cv2.flip(gray, 1)
+    face=profile_cascade.detectMultiScale(gray2, scaleFactor=1.2, minNeighbors=4)
+    for x, y, w, h in face:
+        tab_face.append([width-x, y, width-(x+w), y+h])
+    tab_face=sorted(tab_face, key=operator.itemgetter(0, 1))
+    index=0
+    for x, y, x2, y2 in tab_face:
+        if not index or (x-tab_face[index-1][0]>marge or y-tab_face[index-1][1]>marge):
+            cv2.rectangle(frame, (x, y), (x2, y2), (0, 0, 255), 2)
+        index+=1
+    if cv2.waitKey(1)&0xFF==ord('q'):
+        break
+    fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+    cv2.putText(frame, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+    cv2.imshow('video', frame)
+cap.release()
+cv2.destroyAllWindows()

OpenCV/tutoriel3/visage_camera_v2_raspberry.py

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+import cv2
+import operator
+import picamera
+import picamera.array
+
+face_cascade=cv2.CascadeClassifier("./haarcascade_frontalface_alt2.xml")
+profile_cascade=cv2.CascadeClassifier("./haarcascade_profileface.xml")
+marge=70
+WIDTH=640
+HEIGHT=480
+
+with picamera.PiCamera() as camera:
+    with picamera.array.PiRGBArray(camera) as stream:
+        camera.resolution=(WIDTH, HEIGHT)            
+        while True:
+            camera.capture(stream, 'bgr', use_video_port=True)
+            tab_face=[]
+            tickmark=cv2.getTickCount()
+            gray=cv2.cvtColor(stream.array, cv2.COLOR_BGR2GRAY)
+            face=face_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=4, minSize=(5, 5))
+            for x, y, w, h in face:
+                tab_face.append([x, y, x+w, y+h])
+                face=profile_cascade.detectMultiScale(gray, scaleFactor=1.2, minNeighbors=4)
+                for x, y, w, h in face:
+                    tab_face.append([x, y, x+w, y+h])
+                gray2=cv2.flip(gray, 1)
+                face=profile_cascade.detectMultiScale(gray2, scaleFactor=1.2, minNeighbors=4)
+                for x, y, w, h in face:
+                    tab_face.append([WIDTH-x, y, WIDTH-(x+w), y+h])
+                tab_face=sorted(tab_face, key=operator.itemgetter(0, 1))
+                index=0
+                for x, y, x2, y2 in tab_face:
+                    if not index or (x-tab_face[index-1][0]>marge or y-tab_face[index-1][1]>marge):
+                        cv2.rectangle(stream.array, (x, y), (x2, y2), (0, 0, 255), 2)
+                    index+=1
+            if cv2.waitKey(1)&0xFF==ord('q'):
+                break
+            fps=cv2.getTickFrequency()/(cv2.getTickCount()-tickmark)
+            cv2.putText(stream.array, "FPS: {:05.2f}".format(fps), (10, 30), cv2.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
+            cv2.imshow('video', stream.array)
+            stream.seek(0)
+            stream.truncate()            
+cv2.destroyAllWindows()