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β’
04a893c
1
Parent(s):
81e1d1d
debugging app.py cctv
Browse files
app.py
CHANGED
@@ -354,88 +354,88 @@ def check_database(ima):
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###########################
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def video(vid):
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# # Below VideoWriter object will create
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# # a frame of above defined The output
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# # is stored in 'filename.avi' file.
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#################
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def generate_prompt(AG,facftop,facfmid,facfbot):
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@@ -601,7 +601,8 @@ home""")
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with gr.Column():
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fil1 = gr.File(type="file")
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with gr.Column():
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vid2 = gr.Video()
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hbtn = gr.Button("Video")
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hbtn.click(video, inputs=fil1, outputs=
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demo.launch()
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###########################
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def video(vid):
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return f'Uploaded video name: {vid.name}'
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# file = '../../../../..'+vid.name
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# print(f'file: {file}')
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# # file = vid
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# video = cv2.VideoCapture(file)
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# # video.set(cv2.CAP_PROP_FPS, 10)
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# if (video.isOpened() == False):
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# print("Error reading video file")
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# frame_width = int(video.get(3))
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# frame_height = int(video.get(4))
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# size = (frame_width, frame_height)
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# # # Below VideoWriter object will create
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# # # a frame of above defined The output
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# # # is stored in 'filename.avi' file.
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# result = cv2.VideoWriter('filename.mp4',
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# cv2.VideoWriter_fourcc(*'mp4v'),
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# 10, size)
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# while(True):
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# ret, frame = video.read()
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# if ret == True:
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# rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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# faces = faceCascade.detectMultiScale(rgb,
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# scaleFactor=1.1,
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# minNeighbors=5,
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# minSize=(60, 60),
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# flags=cv2.CASCADE_SCALE_IMAGE)
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# # convert the input frame from BGR to RGB
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# # the facial embeddings for face in input
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# encodings = face_recognition.face_encodings(rgb)
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# names = []
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# # loop over the facial embeddings incase
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# # we have multiple embeddings for multiple fcaes
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# for encoding in encodings:
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# #Compare encodings with encodings in data["encodings"]
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# #Matches contain array with boolean values and True for the embeddings it matches closely
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# #and False for rest
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# matches = face_recognition.compare_faces(data["encodings"],
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# encoding)
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# #set name =inknown if no encoding matches
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# name = "Unknown"
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# # check to see if we have found a match
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# if True in matches:
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# #Find positions at which we get True and store them
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# matchedIdxs = [i for (i, b) in enumerate(matches) if b]
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# counts = {}
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# # loop over the matched indexes and maintain a count for
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# # each recognized face face
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# for i in matchedIdxs:
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# #Check the names at respective indexes we stored in matchedIdxs
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# name = data["names"][i]
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# #increase count for the name we got
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# counts[name] = counts.get(name, 0) + 1
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# #set name which has highest count
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# name = max(counts, key=counts.get)
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# # update the list of names
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# names.append(name)
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# # loop over the recognized faces
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# for ((x, y, w, h), name) in zip(faces, names):
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# # rescale the face coordinates
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# # draw the predicted face name on the image
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# cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
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# cv2.putText(frame, name, (x, y), cv2.FONT_HERSHEY_SIMPLEX,
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# 0.75, (0, 255, 0), 2)
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# result.write(frame)
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# # cv2_imshow(frame)
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# if cv2.waitKey(1) & 0xFF == ord('q'):
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# break
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# # Break the loop
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# else:
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# break
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# # print("The video was successfully saved")
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# return 'filename.mp4'
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#################
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def generate_prompt(AG,facftop,facfmid,facfbot):
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with gr.Column():
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fil1 = gr.File(type="file")
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with gr.Column():
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# vid2 = gr.Video()
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video_name = gr.Text(label="Video Upload")
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hbtn = gr.Button("Video")
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hbtn.click(video, inputs=fil1, outputs=video_name)
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demo.launch()
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