app.py

import gradio as gr
import cv2
from Yolov5_Deepsort.demo import app_main
import sys
import os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))



def process_video(video):
    # 打开视频文件
    cap = cv2.VideoCapture(video)
    # 创建一个 VideoWriter 对象以保存处理后的视频
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    out = cv2.VideoWriter('output.mp4', fourcc, 20.0, (int(cap.get(3)), int(cap.get(4))))

    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        # 处理帧，例如将其转换为灰度
        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        # 将处理后的帧写入输出视频
        out.write(cv2.cvtColor(gray_frame, cv2.COLOR_GRAY2BGR))
    
    cap.release()
    out.release()
    return 'output.mp4'

# Define the title and description
title = "Welcome to DDM DeepSort"
description = "Upload a video to process it using DDM and DeepSORT."

# Initialize Gradio interface with title and description
demo = gr.Interface(
    fn=app_main,
    inputs="video",
    outputs="video",
    title=title,
    description=description
)
html_content = """
<div style="text-align: center;">
    <h1>Welcome to My Video Processing App</h1>
    <p>The author is a third-year undergraduate student at the School of Intelligent Science and Technology, Nanjing University, Suzhou Campus. </p>
    <p>Since this project uses Hugging Face's free CPU, the processing speed is very slow. In the worst case, even a video with a dozen frames can take several minutes to process. Therefore, if possible, it is recommended to deploy on a device with a better GPU.</p>
    <p>Although the YOLOv5 model supports up to 80 classes, my project is primarily focused on autonomous driving. Therefore, objects other than people and cars will be excluded after object detection.</p>
    <p>If this is your first attempt, ensure that the video includes at least people and cars. Additionally, it's recommended that the video is not too long, ideally within 10 seconds.</p>
</div>
"""
with demo:
    gr.HTML(html_content)

demo.launch()