Spaces:
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Gainward777
commited on
Update pages/1_Live_Stream.py
Browse files- pages/1_Live_Stream.py +47 -49
pages/1_Live_Stream.py
CHANGED
@@ -1,12 +1,7 @@
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import
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import os
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import sys
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import streamlit as st
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BASE_DIR = os.path.abspath(os.path.join(__file__, '../../'))
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sys.path.append(BASE_DIR)
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from utils import get_mediapipe_pose
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from process_frame import ProcessFrame
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@@ -14,62 +9,65 @@ from thresholds import get_thresholds_beginner, get_thresholds_pro
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st.title('AI Fitness Trainer: Squats Analysis')
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mode = st.radio('Select Mode', ['Beginner', 'Pro'], horizontal=True)
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thresholds = None
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if mode == 'Beginner':
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thresholds = get_thresholds_beginner()
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elif mode == 'Pro':
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thresholds = get_thresholds_pro()
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live_process_frame = ProcessFrame(thresholds=thresholds, flip_frame=True)
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# Initialize face mesh solution
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pose = get_mediapipe_pose()
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#
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if RTSP_URL:
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ctx = webrtc_streamer(
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key="Squats-pose-analysis",
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video_frame_callback=video_frame_callback,
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rtc_configuration={"iceServers": [{"urls": "stun:stun.l.google.com:19302"}]}, # Add this config
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media_stream_constraints={
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"video": {"frameRate": 30, "deviceId": RTSP_URL},
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"audio": False
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},
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video_html_attrs=VideoHTMLAttributes(autoPlay=True, controls=False, muted=False),
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out_recorder_factory=out_recorder_factory
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)
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download_button = st.empty()
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if os.path.exists(output_video_file):
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with open(output_video_file, 'rb') as op_vid:
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download = download_button.download_button('Download Video', data=op_vid, file_name='output_live.flv')
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if download:
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st.session_state['download'] = True
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if os.path.exists(output_video_file) and st.session_state['download']:
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os.remove(output_video_file)
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st.session_state['download'] = False
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download_button.empty()
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else:
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st.warning("Please provide a valid RTSP stream URL.")
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'''
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import cv2
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import streamlit as st
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import tempfile
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import os
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from utils import get_mediapipe_pose
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from process_frame import ProcessFrame
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st.title('AI Fitness Trainer: Squats Analysis')
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# Select mode
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mode = st.radio('Select Mode', ['Beginner', 'Pro'], horizontal=True)
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thresholds = None
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if mode == 'Beginner':
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thresholds = get_thresholds_beginner()
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elif mode == 'Pro':
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thresholds = get_thresholds_pro()
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# Initialize pose estimation and processing
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live_process_frame = ProcessFrame(thresholds=thresholds, flip_frame=True)
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pose = get_mediapipe_pose()
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# Temporary file to save processed video
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temp_dir = tempfile.TemporaryDirectory()
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output_video_file = os.path.join(temp_dir.name, 'output_live.avi')
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# Initialize video writer
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fourcc = cv2.VideoWriter_fourcc(*'XVID')
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video_writer = None
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# Start video capture
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cap = cv2.VideoCapture(0)
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if not cap.isOpened():
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st.error("Unable to access the camera")
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else:
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stframe = st.empty()
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while True:
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ret, frame = cap.read()
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if not ret:
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st.error("Failed to capture video")
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break
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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processed_frame, _ = live_process_frame.process(frame, pose)
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# Write to video file
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if video_writer is None:
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height, width, _ = processed_frame.shape
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video_writer = cv2.VideoWriter(output_video_file, fourcc, 30, (width, height))
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video_writer.write(cv2.cvtColor(processed_frame, cv2.COLOR_RGB2BGR))
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# Display in Streamlit
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stframe.image(processed_frame, channels="RGB")
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# Stop button
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if st.button("Stop"):
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break
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cap.release()
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if video_writer:
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video_writer.release()
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# Download processed video
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if os.path.exists(output_video_file):
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with open(output_video_file, 'rb') as f:
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st.download_button("Download Processed Video", f, file_name="output_live.avi")
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'''
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