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from flask import Flask, render_template, request, jsonify
import os
import base64
import requests
from PIL import Image
from io import BytesIO
app = Flask(__name__)
# Configuration
UPLOAD_FOLDER = 'static/captures'
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
# Hugging Face API settings
HF_API_TOKEN = os.getenv('HF_API_TOKEN') # Load token from environment variable
HF_API_URL = "https://api-inference.huggingface.co/models/facebook/detr-resnet-50" # Example model for object detection
def query_hugging_face(image_data):
if not HF_API_TOKEN:
raise ValueError("Hugging Face API token not set. Please set the HF_API_TOKEN environment variable.")
headers = {"Authorization": f"Bearer {HF_API_TOKEN}"}
response = requests.post(HF_API_URL, headers=headers, data=image_data)
return response.json()
@app.route('/')
def index():
return render_template('index.html')
@app.route('/capture', methods=['POST'])
def capture():
try:
# Get the base64 image data from the request
data = request.form['image']
header, encoded = data.split(",", 1)
binary_data = base64.b64decode(encoded)
# Save the image
filename = f"capture_{len(os.listdir(app.config['UPLOAD_FOLDER'])) + 1}.jpg"
filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
with open(filepath, "wb") as f:
f.write(binary_data)
# Process with Hugging Face API
with open(filepath, "rb") as f:
hf_result = query_hugging_face(f.read())
# Return the image URL and Hugging Face result
image_url = f"/{filepath}"
return jsonify({
'status': 'success',
'image_url': image_url,
'hf_result': hf_result
})
except Exception as e:
return jsonify({'status': 'error', 'message': str(e)})
if __name__ == '__main__':
app.run(debug=True, host='0.0.0.0', port=7860) |