Update app.py

app.py

@@ -23,15 +23,13 @@ def inference(sample_name):
     age = sample['boneage'].item()
     outputs = session.run(None, {"input": sample['path'].numpy()})
     predicted_age = (outputs[0]*41.172)+127.329
-     # Get the image path and load the image
-    image_path = sample['path'][0]  
-    image = Image.open(image_path)
+    # Get the image data from the MetaTensor and convert it to a format PIL can handle
+    image_data = sample['path'].numpy()
+    image_data = (image_data * 255).astype(np.uint8)  # Assuming the image data is normalized
+    image_data = np.squeeze(image_data)  # Remove any singleton dimensions if necessary
+    image = Image.fromarray(image_data.transpose(1, 2, 0))  # Convert to HWC format
     
-    return {
-        'Bone age': age,
-        'Predicted Bone age': predicted_age[0][0],
-        'Image': image
-    }
+    return age, predicted_age[0][0], image
 
 # List of sample file names
 sample_files = sorted(os.listdir(os.path.join(os.getcwd(),'samples')))