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import os
import gradio as gr
import cv2
import subprocess
from utils import get_mediapipe_pose
from process_frame import ProcessFrame
from thresholds import get_thresholds_beginner, get_thresholds_pro
sample_video = os.path.join(os.path.dirname(__file__), "samples/sample-squats.mp4")
# Initialize face mesh solution
POSE = get_mediapipe_pose()
def process_video(video_path, mode="Beginner"):
output_video_file = f"output_recorded.mp4"
if mode == 'Beginner':
thresholds = get_thresholds_beginner()
elif mode == 'Pro':
thresholds = get_thresholds_pro()
upload_process_frame = ProcessFrame(thresholds=thresholds)
vf = cv2.VideoCapture(video_path)
fps = int(vf.get(cv2.CAP_PROP_FPS))
width = int(vf.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(vf.get(cv2.CAP_PROP_FRAME_HEIGHT))
frame_size = (width, height)
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
video_output = cv2.VideoWriter(output_video_file, fourcc, fps, frame_size)
count = 0
while vf.isOpened():
ret, frame = vf.read()
if not ret:
break
# convert frame from BGR to RGB before processing it.
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
out_frame, _ = upload_process_frame.process(frame, POSE)
video_output.write(cv2.cvtColor(out_frame, cv2.COLOR_RGB2BGR))
if not count%12:
yield out_frame, None
count+=1
vf.release()
video_output.release()
# convertedVideo = f"output_h264.mp4"
# subprocess.call(args=f"ffmpeg -y -i {output_video_file} -c:v libx264 {convertedVideo}".split(" "))
yield None, output_video_file
input_video = gr.Video(label="Input Video")
webcam_video = gr.Video(source="webcam", label="Input Video")
output_frames_up = gr.Image(label="Output Frames")
output_video_file_up = gr.Video(label="Output video")
output_frames_cam = gr.Image(label="Output Frames")
output_video_file_cam = gr.Video(label="Output video")
upload_interface = gr.Interface(
fn=process_video,
inputs=[input_video, gr.Radio(choices=["Beginner", "Pro"], label="Select Mode")],
outputs=[output_frames_up, output_video_file_up],
title=f"AI Fitness Trainer: Squats Analysis",
allow_flagging="never",
examples=[[sample_video]]
)
webcam_interface = gr.Interface(
fn=process_video,
inputs=[webcam_video, gr.Radio(choices=["Beginner", "Pro"], label="Select Mode")],
outputs=[output_frames_cam, output_video_file_cam],
title=f"AI Fitness Trainer: Squats Analysis",
allow_flagging="never"
)
app = gr.TabbedInterface([upload_interface, webcam_interface],
tab_names=["⬆️ Upload Video", "📷️ Live Stream"])
app.queue().launch() |