app.py

import gradio as gr
from ultralytics import YOLO
import cv2

model = YOLO("best.pt")


def detect_image(image):
    results = model(image, conf=0.5)
    return results[0].plot()


def detect_video(video):

    cap = cv2.VideoCapture(video)

    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    fps = int(cap.get(cv2.CAP_PROP_FPS))

    output_path = "output.mp4"

    out = cv2.VideoWriter(
        output_path,
        cv2.VideoWriter_fourcc(*"mp4v"),
        fps,
        (width, height)
    )

    while cap.isOpened():
        ret, frame = cap.read()

        if not ret:
            break

        results = model(frame, conf=0.5)

        annotated = results[0].plot()

        out.write(annotated)

    cap.release()
    out.release()

    return output_path


# ---------------------------
# CUSTOM CSS (your HTML style)
# ---------------------------

css = """

body{
background:linear-gradient(120deg,#f6f9fc,#e9f2ff);
font-family:Segoe UI;
}

.main-container{
max-width:950px;
margin:auto;
background:white;
padding:35px;
border-radius:20px;
box-shadow:0px 10px 30px rgba(0,0,0,0.15);
}

.header{
text-align:center;
font-size:34px;
font-weight:bold;
color:#2c3e50;
}

.subheader{
text-align:center;
font-size:18px;
margin-bottom:20px;
color:#555;
}

.gr-button{
background:#3498db !important;
color:white !important;
border-radius:10px !important;
font-size:18px !important;
padding:12px 30px !important;
}

.gr-button:hover{
background:#217dbb !important;
}

footer{
text-align:center;
margin-top:20px;
color:#777;
font-size:14px;
}
"""


# ---------------------------
# UI
# ---------------------------

with gr.Blocks(css=css) as demo:

    with gr.Column(elem_classes="main-container"):

        gr.Markdown(
        """
        <div class='header'>
        Kurshi's Project 🙋🏻‍♀️✨
        </div>

        <div class='header'>
        Object Detection in Autonomous Vehicles 🚗
        </div>

        <div class='subheader'>
        YOLO Object Detection
        </div>
        """
        )

        with gr.Tabs():

            with gr.Tab("Upload Image"):

                input_img = gr.Image(
                    type="numpy",
                    label="Upload Image"
                )

                detect_btn = gr.Button("Start Detection")

                output_img = gr.Image(label="Detection Result")

                detect_btn.click(
                    detect_image,
                    inputs=input_img,
                    outputs=output_img
                )

            with gr.Tab("Upload Video"):

                input_video = gr.Video(label="Upload Video")

                video_btn = gr.Button("Start Detection")

                output_video = gr.Video(label="Detection Result")

                video_btn.click(
                    detect_video,
                    inputs=input_video,
                    outputs=output_video
                )

        gr.Markdown(
        """
        <footer>
        YOLO | Self Driving Car Dataset | STET College
        </footer>
        """
        )


demo.launch(server_name="0.0.0.0", server_port=7860, share = True)