image_recognition api added

Author: theshubh007

Flask_Apis/.gitignore

@@ -0,0 +1,42 @@
+import numpy as np
+from flask import Flask, request, jsonify, render_template,json
+import cv2
+from skimage.metrics import structural_similarity as ssim
+
+
+
+app = Flask(__name__)
+
+@app.route('/')
+def home():
+    return jsonify({'message':'Welcome to Flask Apis'})
+
+@app.route('/img',methods=['POST'])
+def predict():
+    file1 = request.files['file1']
+    file2 = request.files['file2']
+
+    # Read the images using OpenCV
+    img1 = cv2.imdecode(np.frombuffer(file1.read(), np.uint8), cv2.IMREAD_COLOR)
+    img2 = cv2.imdecode(np.frombuffer(file2.read(), np.uint8), cv2.IMREAD_COLOR)
+
+    # Resize the images to 256x256 pixels
+    img1 = cv2.resize(img1, (256, 256))
+    img2 = cv2.resize(img2, (256, 256))
+
+    # Convert the images to grayscale
+    gray_img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+    gray_img2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+
+    # Calculate the structural similarity index between the images
+    score = ssim(gray_img1, gray_img2, full=True)[0]
+
+    # Convert the similarity score to a percentage
+    similarity_percentage = score * 100
+
+    # Return the similarity percentage in a JSON response
+    return jsonify({'similarity_percentage': similarity_percentage})    
+
+
+if __name__ == '__main__':
+    app.run(debug=True)