Update app.py

app.py

@@ -26,11 +26,7 @@ brain_tumor_classifier = pipeline("image-classification", model="Devarshi/Brain_
 
 # Create a function to Detect/Classify Alzheimer
 def classify_alzheimer(image):
-    with open(image, 'rb') as img:
-        encoded_string = base64.b64encode(img.read())
-    image_base = encoded_string.decode('utf-8')
-    
-    result = alzheimer_classifier(image_base)
+    result = alzheimer_classifier(image)
     prediction = result[0]
     score = prediction['score']
     label = prediction['label']
@@ -72,7 +68,7 @@ with gr.Blocks(theme=theme) as Alzheimer:
         with gr.Column():
             gr.Markdown("# Alzheimer Detection and Classification")
             gr.Markdown("> Classify the alzheimer into Mild Demented, Very Mild Demented, Moderate Demented and Non Demented.")
-            image = gr.Image()
+            image = gr.Image(type="pil")
             output = gr.Label(label='Alzheimer Classification', container=True, scale=2)
             with gr.Row():
                 gr.ClearButton([image, output])
@@ -105,7 +101,7 @@ with gr.Blocks(theme=theme) as BreastCancer:
         with gr.Column():
             gr.Markdown("# Breast Cancer Detection and Classification")
             gr.Markdown("> Classify the breast cancer.")
-            image = gr.Image()
+            image = gr.Image(type="pil")
             output = gr.Label(label='Breast Cancer Classification', container=True, scale=2)
             with gr.Row():
                 button = gr.Button(value="Submit", variant="primary")
@@ -139,7 +135,7 @@ with gr.Blocks(theme=theme) as BrainTumor:
         with gr.Column():
             gr.Markdown("# Brain Tumor Detection and Classification")
             gr.Markdown("> Classify the Brain Tumor.")
-            image = gr.Image()
+            image = gr.Image(type="pil")
             output = gr.Label(label='Brain_Tumor Classification', container=True, scale=2)
             with gr.Row():
                 button = gr.Button(value="Submit", variant="primary")