Add files via upload

new.py

@@ -0,0 +1,29 @@
+import cv2
+import  cvzone
+cap = cv2.VideoCapture(0)
+cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+eye_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye_tree_eyeglasses.xml')
+num=1
+while True:
+    k=cv2.waitKey(100)
+    if k==ord('s'):
+        num=num+1
+    print(num)    
+    if(num<=29):
+              overlay = cv2.imread(f'static/Glasses/glass3.png', cv2.IMREAD_UNCHANGED)
+            # overlay = cv2.imread('static/Glasses/glass6.png'.format(num), cv2.IMREAD_UNCHANGED)
+
+    _, frame = cap.read()
+    gray_scale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    faces = cascade.detectMultiScale(gray_scale)
+    for (x, y, w, h) in faces:
+        #cv2.rectangle(frame,(x, y), (x+w, y+h), (0, 255, 0), 2)
+        overlay_resize = cv2.resize(overlay,(w,int(h*0.8)))
+        frame = cvzone.overlayPNG(frame, overlay_resize, [x, y])
+    cv2.imshow('SnapLens', frame)
+    if cv2.waitKey(10) == ord('q') or num>29:
+        break
+
+
+cap.release()
+cv2.destroyAllWindows()

tryon.py

@@ -0,0 +1,64 @@
+from flask import Flask, render_template, request, redirect, url_for
+import cv2
+import os
+
+app = Flask(__name__)
+app.config['UPLOAD_FOLDER'] = 'static/uploads'
+
+glasses_overlay = None  
+
+@app.route('/')
+def upload():
+    return render_template("index.html")
+
+@app.route('/success', methods=['POST'])
+def success():
+    global glasses_overlay
+
+    if request.method == 'POST':
+        f = request.files['file']
+        uploaded_path = os.path.join(app.config['UPLOAD_FOLDER'], f.filename)
+        f.save(uploaded_path)
+
+        # Load the uploaded image using OpenCV
+        glasses_overlay = cv2.imread(uploaded_path, cv2.IMREAD_UNCHANGED)
+
+    return redirect(url_for('tryon'))
+
+@app.route('/tryon', methods=['GET'])
+def tryon():
+    if glasses_overlay is None:
+        return "Please upload an image first."
+
+    cap = cv2.VideoCapture(0)  # Open webcam
+    face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_alt2.xml')
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        gray_scale = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        faces = face_cascade.detectMultiScale(gray_scale, scaleFactor=1.1, minNeighbors=5)
+
+        for (x, y, w, h) in faces:
+            overlay_resize = cv2.resize(glasses_overlay, (w, int(h * 0.8)))
+
+            for i in range(overlay_resize.shape[0]):
+                for j in range(overlay_resize.shape[1]):
+                    if overlay_resize[i, j, 3] != 0:  # Check the alpha channel
+                        frame[y + i, x + j, :3] = overlay_resize[i, j, :3]  # Overlay glasses image
+
+        cv2.imshow('Virtual Try-On', frame)
+
+        if cv2.waitKey(10) == ord('e'):
+            break
+
+    cap.release()
+    cv2.destroyAllWindows()
+
+    return "Virtual try-on completed."
+
+
+if __name__ == '__main__':
+    app.run(debug=True)