app.py

import cv2
from cvzone.PoseModule import PoseDetector
import gradio as gr
import tempfile
import os

# Initialize pose detector
poseDetector = PoseDetector()

# Function to process video and detect poses
def process_video(video_path):
    cap = cv2.VideoCapture(video_path)
    if not cap.isOpened():
        raise ValueError("Could not open video file.")

    # Get video properties
    fps = int(cap.get(cv2.CAP_PROP_FPS))
    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))

    # Create a temporary file to save the processed video
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
    temp_path = temp_file.name
    temp_file.close()

    # Initialize video writer
    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
    out = cv2.VideoWriter(temp_path, fourcc, fps, (width, height))

    posList = []

    while True:
        success, img = cap.read()
        if not success:
            break

        # Detect pose
        img = poseDetector.findPose(img)
        lmList, bboxInfo = poseDetector.findPosition(img)

        if bboxInfo:
            lmString = ''
            for lm in lmList:
                lmString += f'{lm[0]},{img.shape[0]-lm[1]},{lm[2]},'
            posList.append(lmString)

        # Write the processed frame to the output video
        out.write(img)

    # Release video capture and writer
    cap.release()
    out.release()

    # Save pose data to a file
    with open("AnimationFile.txt", "w") as f:
        f.writelines(["%s\n" % item for item in posList])

    # Return the processed video path and frames (empty list for now)
    return temp_path, []

# Gradio interface
def gradio_interface(video):
    processed_video_path, _ = process_video(video)
    return processed_video_path

# Create Gradio app
iface = gr.Interface(
    fn=gradio_interface,
    inputs=gr.Video(label="Input Video"),
    outputs=gr.Video(label="Processed Video"),
    title="Pose Detection with MediaPipe",
    description="Upload a video to detect human poses using MediaPipe and OpenCV.",
)

# Launch the app with a public link
iface.launch(share=True)