71 lines
2.6 KiB
Python
71 lines
2.6 KiB
Python
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import tensorflow as tf
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import cv2
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import os
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import numpy as np
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import random
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import common
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th1=30
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th2=55
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video_dir="dashcam Cedric"
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tab_panneau, tab_image_panneau=common.lire_images_panneaux(common.dir_images_panneaux)
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model_is_panneau=common.is_panneau_model()
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checkpoint=tf.train.Checkpoint(model_is_panneau=model_is_panneau)
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checkpoint.restore(tf.train.latest_checkpoint("./training_is_panneau/"))
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model_panneau=common.panneau_model(len(tab_panneau))
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checkpoint=tf.train.Checkpoint(model_panneau=model_panneau)
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checkpoint.restore(tf.train.latest_checkpoint("./training_panneau/"))
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l=os.listdir(video_dir)
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random.shuffle(l)
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for video in l:
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if not video.endswith("mp4"):
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continue
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cap=cv2.VideoCapture(video_dir+"/"+video)
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print("video:", video)
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id_panneau=-1
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while True:
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ret, frame=cap.read()
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if ret is False:
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break
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f_w, f_h, f_c=frame.shape
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frame=cv2.resize(frame, (int(f_h/1.5), int(f_w/1.5)))
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image=frame[200:400, 700:1000]
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cv2.rectangle(frame, (700, 200), (1000, 400), (255, 255, 255), 1)
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gray=cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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circles=cv2.HoughCircles(gray, cv2.HOUGH_GRADIENT, 1, 20, param1=th1, param2=th2, minRadius=5, maxRadius=45)
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if circles is not None:
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circles=np.int16(np.around(circles))
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for i in circles[0,:]:
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if i[2]!=0:
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panneau=cv2.resize(image[max(0, i[1]-i[2]):i[1]+i[2], max(0, i[0]-i[2]):i[0]+i[2]], (common.size, common.size))/255
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cv2.imshow("panneau", panneau)
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prediction=model_is_panneau(np.array([panneau]), training=False)
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print("prediction", prediction)
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if prediction[0][0]>0.9:
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prediction=model_panneau(np.array([panneau]), training=False)
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id_panneau=np.argmax(prediction[0])
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print("panneau", prediction, id_panneau, tab_panneau[id_panneau])
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w, h, c=tab_image_panneau[id_panneau].shape
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if id_panneau!=-1:
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frame[0:h, 0:w, :]=tab_image_panneau[id_panneau]
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cv2.putText(frame, "fichier:"+video, (30, 30), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 255, 0), 1, cv2.LINE_AA)
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cv2.imshow("Video", frame)
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key=cv2.waitKey(1)&0xFF
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if key==ord('q'):
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quit()
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if key==ord('a'):
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for cpt in range(100):
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ret, frame=cap.read()
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if key==ord('f'):
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break
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cv2.destroyAllWindows()
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