Update app.py

app.py

@@ -18,9 +18,9 @@ st.title("Welcome to Sports Person Classifier!")
 
 
 
-def classify_image(image_base64_data, image=None):
+def classify_image(image_base64_data, file_path=None):
 
-    imgs = get_cropped_image_if_2_eyes_new(image, image_base64_data)
+    imgs = get_cropped_image_if_2_eyes_new(file_path, image_base64_data)
 
     result = []
     for img in imgs:
@@ -41,12 +41,12 @@ def classify_image(image_base64_data, image=None):
     return result
 
 
-def get_cropped_image_if_2_eyes_new(image, image_base64_data):
+def get_cropped_image_if_2_eyes_new(file_path, image_base64_data):
     face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
     eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
 
-    if image:
-        img = image
+    if file_path:
+        img = cv2.imread(file_path)
     else:
         img = get_cv2_image_from_base64_string(image_base64_data)
 
@@ -121,17 +121,18 @@ def save_uploaded_image(uploaded_image):
     try:
         with open(uploaded_image.name, 'wb') as f:
             f.write(uploaded_image.getbuffer())
-        return True
+        return {"complete":True, "filename":"uploaded_image.name"}
     except:
-        return False
+        return {"complete":False, "filename":"uploaded_image.name"}
 
 
 uploaded_image = st.file_uploader('Choose an image')
 
 if uploaded_image is not None:
     # save the image in a directory
-    if save_uploaded_image(uploaded_image):
-        display_image = Image.open(uploaded_image)
+    image_dict = save_uploaded_image(uploaded_image)
+    if image_dict["complete"]:
+        display_image = image_dict["filename"]
         st.header("Image Uploded!, Processing...")
         load_saved_artifacts()
         st.text(classify_image(get_b64_test_image_for_virat(), display_image))