Final version of backend and frontend

1 files changed, 0 insertions, 77 deletions

diff --git a/backend/app.py b/backend/app.py
deleted file mode 100644
index 4ed4954..0000000
--- a/backend/app.py
+++ /dev/null
@@ -1,77 +0,0 @@
-import os
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-import boto3
-import cv2
-import tempfile
-import numpy as np
-
-app = Flask(__name__)
-CORS(app)
-
-# Configure AWS S3
-s3 = boto3.client('s3')
-BUCKET_NAME_ORIGINAL = "original-images-rapid-macaw"
-BUCKET_NAME_PROCESSED = "processed-images-rapid-macaw"
-
-@app.route('/upload', methods=['POST'])
-def upload_file():
-    if 'image' not in request.files:
-        return jsonify({'error': 'No file provided'}), 400
-    
-    file = request.files['image']
-    operation = request.form.get('operation', 'edge_detection')  # Default to edge detection
-    if file and allowed_file(file.filename):
-        # Save the file temporarily
-        temp_file = tempfile.NamedTemporaryFile(delete=False)
-        file.save(temp_file.name)
-
-        # Upload to S3 original bucket
-        with open(temp_file.name, "rb") as img_data:
-            s3.put_object(Bucket=BUCKET_NAME_ORIGINAL, Key=file.filename, Body=img_data, ContentType="image/png")
-
-        # Fetch the image from the original bucket
-        original_img_obj = s3.get_object(Bucket=BUCKET_NAME_ORIGINAL, Key=file.filename)
-        original_img_data = original_img_obj['Body'].read()
-
-        # Process the image
-        processed_image_path = process_image(original_img_data, operation)
-
-        # Upload processed image to S3 processed bucket
-        processed_filename = f"processed_{file.filename}"
-        with open(processed_image_path, "rb") as processed_img_data:
-            s3.put_object(Bucket=BUCKET_NAME_PROCESSED, Key=processed_filename, Body=processed_img_data, ContentType="image/png")
-
-        # Clean up temporary files
-        os.remove(temp_file.name)
-        os.remove(processed_image_path)
-
-        processed_file_url = f'https://{BUCKET_NAME_PROCESSED}.s3.amazonaws.com/{processed_filename}'
-
-        return jsonify({'message': 'File processed and uploaded successfully', 'processed_file': processed_file_url}), 200
-    else:
-        return jsonify({'error': 'Invalid file type'}), 400
-
-def allowed_file(filename):
-    return '.' in filename and filename.rsplit('.', 1)[1].lower() in {'png', 'jpg', 'jpeg'}
-
-def process_image(image_data, operation):
-    # Convert image data to numpy array
-    nparr = np.frombuffer(image_data, np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-
-    processed_img = img
-
-    if operation == 'edge_detection':
-        processed_img = cv2.Canny(img, 100, 200)
-    elif operation == 'color_inversion':
-        processed_img = cv2.bitwise_not(img)
-
-    # Save processed image to a temporary path
-    output_path = os.path.join(tempfile.gettempdir(), f'processed_image.png')
-    cv2.imwrite(output_path, processed_img)
-
-    return output_path
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5000, debug=True)