app.py

from flask import Flask, render_template, request, redirect, url_for
from transformers import DetrImageProcessor, DetrForObjectDetection
from PIL import Image, ImageDraw
import torch
import os
import uuid

app = Flask(__name__)

# Set upload folder
UPLOAD_FOLDER = 'static/uploads'
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER

# Load DETR model and processor
processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/upload', methods=['POST'])
def upload_file():
    if 'file' not in request.files:
        return redirect(request.url)
    file = request.files['file']
    if file.filename == '':
        return redirect(request.url)
    
    # Save the uploaded file
    filename = str(uuid.uuid4()) + os.path.splitext(file.filename)[1]
    filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
    file.save(filepath)
    
    # Process image for object detection
    image = Image.open(filepath).convert("RGB")
    inputs = processor(images=image, return_tensors="pt")
    outputs = model(**inputs)
    
    # Post-process outputs
    target_sizes = torch.tensor([image.size[::-1]])
    results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
    
    # Draw bounding boxes
    draw = ImageDraw.Draw(image)
    for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
        box = [round(i, 2) for i in box.tolist()]
        label_str = model.config.id2label[label.item()]
        draw.rectangle(box, outline="red", width=3)
        draw.text((box[0], box[1]), f"{label_str}: {score:.2f}", fill="red")
    
    # Save output image
    output_filename = f"output_{filename}"
    output_filepath = os.path.join(app.config['UPLOAD_FOLDER'], output_filename)
    image.save(output_filepath)
    
    return render_template('results.html', original_image=url_for('static', filename=f'uploads/{filename}'),
                          processed_image=url_for('static', filename=f'uploads/{output_filename}'))

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=7860)