Update package in req.txt

app.py

@@ -15,10 +15,10 @@ from facenet_pytorch import MTCNN
 model_file_path = 'models/bmi.h5'
 model = tf.keras.models.load_model(model_file_path)
 
-mtcnn2 = MTCNN(
-        image_size=160, margin=40, min_face_size=20,
-        thresholds=[0.6, 0.7, 0.7], factor=0.709, post_process=False
-    )
+# mtcnn2 = MTCNN(
+#         image_size=160, margin=40, min_face_size=20,
+#         thresholds=[0.6, 0.7, 0.7], factor=0.709, post_process=False
+#     )
 
 # Preprocess the images for VGG16
 def preprocess_image(img_path):
@@ -38,13 +38,13 @@ def main():
 
     if img_file_buffer is not None:
         # To read image file buffer as a PIL Image:
-        img = Image.open(img_file_buffer)
+        # img = Image.open(img_file_buffer)
 
-        detected_image = Image.fromarray(mtcnn2(img).numpy().transpose(1, 2, 0).astype(np.uint8))
-        st.image(detected_image, caption="Detected Face")
+        # detected_image = Image.fromarray(mtcnn2(img).numpy().transpose(1, 2, 0).astype(np.uint8))
+        # st.image(detected_image, caption="Detected Face")
         
         embeddings = preprocess_image(img_file_buffer)
-        bmi = round(model.predict(embeddings), 2) - 4
+        bmi = model.predict(embeddings)
         st.write(f"Your BMI is {bmi}")
 
 if __name__ == '__main__':