app.py

from flask import Flask, request, jsonify, render_template
from flask_cors import CORS
import numpy as np
import cv2
import base64
from src.core import process_inpaint, s_image
import os

app = Flask(__name__)
CORS(app) 

# Add the API URL
API_URL = os.environ.get("API_URL", "https://walidadebayo-image-eraser-api.hf.space/") 

# endpoint for health checks
@app.route('/', methods=['GET'])
def health_check():
    # For browser requests, return HTML documentation
    if request.headers.get('Accept', '').find('text/html') != -1:
        return render_template('index.html', api_url=API_URL)
    
    # For API health checks, return JSON
    return jsonify({"status": "API is running"})

@app.route('/api/inpaint', methods=['POST'])
def inpaint():
    # Get data from request
    data = request.json
    image_data = data.get('image')
    mask_data = data.get('mask')
    
    # Convert base64 to numpy arrays
    image = base64_to_image(image_data)
    mask = base64_to_image(mask_data)
    
    # Process the image
    result = process_inpaint(image, mask)
    
    # Convert back to base64
    result_base64 = image_to_base64(result)
    
    return jsonify({'result': result_base64})

@app.route('/api/seam-carve', methods=['POST'])
def seam_carve():
    # Get data from request
    data = request.json
    image_data = data.get('image')
    mask_data = data.get('mask')
    vs = int(data.get('vs', 0))  # vertical seams
    hs = int(data.get('hs', 0))  # horizontal seams
    mode = data.get('mode', 'resize')  # resize or remove
    
    # Convert base64 to numpy arrays
    image = base64_to_image(image_data)
    mask = base64_to_image(mask_data)
    
    # Process the image
    result = s_image(image, mask, vs, hs, mode)
    
    # Convert back to base64
    result_base64 = image_to_base64(result)
    
    return jsonify({'result': result_base64})

def base64_to_image(base64_str):
    img_bytes = base64.b64decode(base64_str.split(',')[1])
    img_array = np.frombuffer(img_bytes, np.uint8)
    img = cv2.imdecode(img_array, cv2.IMREAD_UNCHANGED)
    return img

def image_to_base64(image):
    # Convert float types to uint8
    if image.dtype == np.float64 or image.dtype == np.float32:
        # Normalize to 0-255 range and convert to uint8
        image = np.clip(image * 255 if image.max() <= 1.0 else image, 0, 255).astype(np.uint8)
    
    # Convert to BGR if it's RGB
    if len(image.shape) > 2 and image.shape[2] == 3:
        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
    
    _, buffer = cv2.imencode('.png', image)
    img_bytes = base64.b64encode(buffer).decode('utf-8')
    return f"data:image/png;base64,{img_bytes}"

if __name__ == '__main__':
    port = int(os.environ.get("PORT", 7860))
    app.run(debug=True, host='0.0.0.0', port=port)