Update app.py

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 from transformers import pipeline
+from PIL import Image
 import cv2
 import numpy as np
 import requests
@@ -18,26 +19,32 @@ API_KEY = os.getenv("API_KEY")
 
 # BRAIN_TUMOR_API_URL = "https://api-inference.huggingface.co/models/Devarshi/Brain_Tumor_Classification"
 BREAST_CANCER_API_URL = "https://api-inference.huggingface.co/models/MUmairAB/Breast_Cancer_Detector"
-ALZHEIMER_API_URL = "https://api-inference.huggingface.co/models/dewifaj/alzheimer_mri_classification"
+# ALZHEIMER_API_URL = "https://api-inference.huggingface.co/models/dewifaj/alzheimer_mri_classification"
 headers = {"Authorization": "Bearer "+API_KEY+"", 'Content-Type': 'application/json'}
-# alzheimer_classifier = pipeline("image-classification", model="dewifaj/alzheimer_mri_classification")
+alzheimer_classifier = pipeline("image-classification", model="dewifaj/alzheimer_mri_classification")
 # breast_cancer_classifier = pipeline("image-classification", model="MUmairAB/Breast_Cancer_Detector")
 brain_tumor_classifier = pipeline("image-classification", model="Devarshi/Brain_Tumor_Classification")
 
 # Create a function to Detect/Classify Alzheimer
 def classify_alzheimer(image):
-    image_data = np.array(image, dtype=np.uint8)
-    _, buffer = cv2.imencode('.jpg', image_data)
-    binary_data = buffer.tobytes()
-
-    response = requests.post(ALZHEIMER_API_URL, headers=headers, data=binary_data)
-    result = {}
-    print(response.json())
-    for ele in response.json():
-        label, score = ele.values()
-        result[label] = score
-
-    return result
+    # image_data = np.array(image, dtype=np.uint8)
+    # _, buffer = cv2.imencode('.jpg', image_data)
+    # binary_data = buffer.tobytes()
+
+    # response = requests.post(ALZHEIMER_API_URL, headers=headers, data=binary_data)
+    # result = {}
+    # print(response.json())
+    # for ele in response.json():
+    #     label, score = ele.values()
+    #     result[label] = score
+
+    # return result
+    image_pil = Image.open(image)
+    result = alzheimer_classifier(image)
+    prediction = result[0]
+    score = prediction['score']
+    label = prediction['label']
+    return {"score": score, "label": label}
 
 
 # Create a function to Detect/Classify Breast_Cancer