app.py

import importlib
import gradio as gr
from PIL import Image
import cv2
import os

# Sample media paths and thumbnails
sample_images = {
    "Unorganized": "samples/unorganized.jpg",
    "Organized": "samples/organized.jpg"
}

sample_videos = {
    "Sample Video": "samples/sample_video.mp4"
}

def load_model(model_name):
    module = importlib.import_module(model_name)
    return module

models = {
    "Multi-class model": "model_1",
    "Empty class": "model_2",
    "Misalignment class": "model_3"
}

def detect_image(model_choice, input_image=None, sample_image_choice=None):
    model = load_model(models[model_choice])
    if sample_image_choice:
        input_image = Image.open(sample_images[sample_image_choice])
    return model.detect_image(input_image)

def detect_video(model_choice, input_video=None, sample_video_choice=None):
    model = load_model(models[model_choice])
    if sample_video_choice:
        input_video = sample_videos[sample_video_choice]

    output_video_path = model.detect_video(input_video)
    return output_video_path

app = gr.Blocks()

with app:
    gr.Markdown("## Object Detection using TensorFlow Lite Models")
    with gr.Row():
        model_choice = gr.Dropdown(label="Select Model", choices=list(models.keys()), value="Multi-class model")
        
        with gr.Tab("Image Detection"):
            with gr.Column():
                image_input = gr.Image(type="pil", label="Upload an image (or use sample)")
                sample_image_choice = gr.Dropdown(
                    label="Or select a sample image",
                    choices=[None] + list(sample_images.keys()),
                    value=None
                )
                image_output = gr.Image(type="pil", label="Detection Result")
                gr.Button("Submit Image").click(
                    fn=detect_image, 
                    inputs=[model_choice, image_input, sample_image_choice], 
                    outputs=image_output
                )
        
        with gr.Tab("Video Detection"):
            with gr.Column():
                video_input = gr.Video(label="Upload a video (or use sample)")
                sample_video_choice = gr.Dropdown(
                    label="Or select a sample video",
                    choices=[None] + list(sample_videos.keys()),
                    value=None
                )
                video_output = gr.Video(label="Detection Result")
                gr.Button("Submit Video").click(
                    fn=detect_video, 
                    inputs=[model_choice, video_input, sample_video_choice], 
                    outputs=video_output
                )

app.launch(share=True)