# !pip install timm
# !pip install transformers
# !pip install pillow
# !pip install gradio

from PIL import Image, ImageDraw
import gradio as gr
from transformers import pipeline

# Initialize the object detection pipeline
object_detector = pipeline("object-detection", model="facebook/detr-resnet-50")

def detect_objects(image):
    # Perform object detection on the input image
    results = object_detector(image)

    # Create a draw object
    draw = ImageDraw.Draw(image)

    # Draw bounding boxes around detected objects
    for result in results:
        label = result['label']
        score = result['score']
        box = result['box']

        # Draw the bounding box
        draw.rectangle(
            [(box['xmin'], box['ymin']), (box['xmax'], box['ymax'])],
            outline="red", width=2
        )

        # Draw the label and score
        draw.text((box['xmin'], box['ymin']), f"{label} {score:.2f}", fill="white",size=20)

    return image

# Create the Gradio interface
interface = gr.Interface(
    fn=detect_objects,
    inputs=gr.Image(type="pil"),
    outputs=gr.Image(type="pil"),
    title="Image Object Detector",
    description="Upload an image to detect objects using the DETR model."
)

# Launch the app
interface.launch()