Update app.py

app.py

@@ -1,53 +1,53 @@
-from flask import Flask, render_template, request
-import numpy as np
-import os
-import cv2
-import tensorflow
-
-
-model_path = os.path.join(os.path.dirname(__file__), "model.h5")
-model = tensorflow.keras.models.load_model(model_path, compile=False, safe_mode=False)
-
-
-
-app = Flask(__name__)
-
-UPLOAD_FOLDER = 'static/uploads'
-ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', "webp"}
-
-app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
-os.makedirs(UPLOAD_FOLDER, exist_ok=True)
-
-def allowed_file(filename):
-    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
-
-@app.route('/')
-def form():
-    return render_template('index.html')
-@app.route('/predict', methods=['POST'])
-def predict():
-    if 'file' not in request.files:
-        return "No file uploaded", 400
-
-    file = request.files['file']
-    
-    if file.filename == '' or not allowed_file(file.filename):
-        return "Invalid file type", 400
-
-    file_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
-    file.save(file_path)
-
-    image = cv2.imread(file_path)
-    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-    image = cv2.resize(image, (256, 256))
-    image = image.astype('float32') / 255.0  
-    image = np.expand_dims(image, axis=0) 
-
-    result = float(model.predict(image))
-    prediction = "No Mask" if result > 0.5 else "With Mask"
-
-    return render_template('predict.html', result=prediction)
-
-if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 5000)) 
-    app.run(host="0.0.0.0", port=port)
+from flask import Flask, render_template, request
+import numpy as np
+import os
+import cv2
+import tensorflow
+
+
+model_path = os.path.join(os.path.dirname(__file__), "model.h5")
+model = tensorflow.keras.models.load_model(model_path, compile=False, safe_mode=False)
+
+
+
+app = Flask(__name__)
+
+UPLOAD_FOLDER = 'static/uploads'
+ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', "webp"}
+
+app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+
+def allowed_file(filename):
+    return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
+
+@app.route('/')
+def form():
+    return render_template('index.html')
+@app.route('/predict', methods=['POST'])
+def predict():
+    if 'file' not in request.files:
+        return "No file uploaded", 400
+
+    file = request.files['file']
+    
+    if file.filename == '' or not allowed_file(file.filename):
+        return "Invalid file type", 400
+
+    file_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
+    file.save(file_path)
+
+    image = cv2.imread(file_path)
+    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    image = cv2.resize(image, (256, 256))
+    image = image.astype('float32') / 255.0  
+    image = np.expand_dims(image, axis=0) 
+
+    result = float(model.predict(image))
+    prediction = "No Mask" if result > 0.5 else "With Mask"
+
+    return render_template('predict.html', result=prediction)
+
+if __name__ == "__main__":
+    port = int(os.environ.get("PORT", 7860)) 
+    app.run(host="0.0.0.0", port=port)