first commit

app.py

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+from flask import Flask,render_template, request, redirect, url_for, make_response,jsonify
+from werkzeug.utils import secure_filename
+import os
+from skimage.metrics import structural_similarity
+import imutils
+import cv2
+from PIL import Image
+
+
+ALLOWED_EXTENSIONS = set(['png','jpg','JPG','PNG'])
+
+def allowed_file(filename):
+    return '.' in filename and filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS
+
+app = Flask(__name__)
+
+@app.route('/', methods=['POST','GET'])
+def index():
+    if request.method == 'GET':
+        return render_template('index.html')
+    if request.method == 'POST':
+        f = request.files['file_upload']
+
+        if not (f and allowed_file(f.filename)):
+            return jsonify({"error": 1001, "msg": "please check yout file type (only except JPG, PNG, jpg, png files)"})
+
+        base_path = os.path.dirname(__file__)
+
+
+        upload_path = os.path.join(base_path, 'images/upload_image', secure_filename(f.filename))
+        f.save(upload_path)
+
+        uploaded_img = Image.open(upload_path).resize((250,160))
+
+        uploaded_img.save(os.path.join(base_path,'images/upload_image','tampered.jpg'))
+
+        original_img = Image.open(os.path.join(base_path,'images/origin_image','origin1.jpg')).resize((250,160))
+        original_img.save(os.path.join(base_path,'images/origin_image','origin1.jpg'))
+
+
+
+        origin_img = cv2.imread(os.path.join(base_path,'images/origin_image','origin1.jpg'))
+        upload_img = cv2.imread(os.path.join(base_path,'images/upload_image','tampered.jpg'))
+
+
+        original_grey = cv2.cvtColor(origin_img,cv2.COLOR_BGR2GRAY)
+        uploaded_grey = cv2.cvtColor(upload_img,cv2.COLOR_BGR2GRAY)
+
+        # Compute the structural similarity Index (SSIM) between the two images, ensuring that the difference image is returned
+        (score, diff)= structural_similarity(original_grey, uploaded_grey, full=True)
+        diff = (diff * 255).astype("uint8")
+
+        # Calculating threshold and contours
+        thresh = cv2.threshold(diff, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
+        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cnts = imutils.grab_contours(cnts)
+
+
+        #loop over the contours
+        for c in cnts:
+        # applying contours on image 
+            (x, y, w, h) = cv2.boundingRect(c)
+            cv2.rectangle(origin_img, (x,y), (x+w, y+h), (0, 0, 255), 2)
+            cv2.rectangle(upload_img, (x,y), (x+y, y+h), (0, 0, 255), 2)
+
+        cv2.imwrite(os.path.join(base_path,'static/generated','image_original1.jpg'),origin_img)
+        cv2.imwrite(os.path.join(base_path,'static/generated','image_uploaded1.jpg'),upload_img)
+        cv2.imwrite(os.path.join(base_path,'static/generated','diff1.jpg'),diff)
+        cv2.imwrite(os.path.join(base_path,'static/generated','thresh1.jpg'),thresh)
+
+        return render_template('index_ok.html',pred=str(round(score*100,2))+ '%' + 'correct')
+
+
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=8987, debug=False)