undone convert to unint8

app.py

@@ -22,7 +22,6 @@ LABELS = [
     "Colorectal Adenocarcinoma Epithelium",
 ]
 
-
 model = Predictor(n_labels=len(LABELS))
 
 model_file = hf_hub_download(
@@ -61,8 +60,10 @@ number_of_examples = len(labels)
 os.makedirs("ui_examples", exist_ok=True)
 
 for i in range(number_of_examples):
+
     img_array = images[i]
     val_img_arr = val_images[i]
+
     label_index = int(labels[i].item() if hasattr(labels[i], 'item') else labels[i])
     val_label_index = int(val_labels[i].item() if hasattr(val_labels[i], 'item') else val_labels[i])
     
@@ -72,8 +73,8 @@ for i in range(number_of_examples):
     file_path = f"ui_examples/sample_{i}.jpg"
     val_file_path = f"ui_examples/val_sample_{i}.jpg"
 
-    Image.fromarray(img_array.astype("uint8"), "RGB").save(file_path)
-    Image.fromarray(val_img_arr.astype("uint8"), "RGB").save(val_file_path)
+    Image.fromarray(img_array, "RGB").save(file_path)
+    Image.fromarray(val_img_arr, "RGB").save(val_file_path)
 
     example_rows_test.append([file_path, truth_label_text])
     example_rows_val.append([val_file_path, val_truth_label_text])
@@ -123,7 +124,7 @@ with gradio.Blocks(css=custom_css) as demo:
         with gradio.Row():
             input_img = gradio.Image(height=512, width=512)
             with gradio.Column():
-                output_lbl = gradio.Label(num_top_classes=3)
+                output_lbl = gradio.Label(num_top_classes=5)
                 btn = gradio.Button("Predict")
                 btn.click(fn=predict, inputs=input_img, outputs=output_lbl)
 
@@ -134,7 +135,7 @@ with gradio.Blocks(css=custom_css) as demo:
             with gradio.Column():
                 input_img_ex = gradio.Image(label="Selected Test Image", height=512, width=512)
                 truth_box = gradio.Textbox(label="Ground Truth Label", interactive=False)
-            output_lbl_ex = gradio.Label(num_top_classes=3, label="Model Prediction")
+            output_lbl_ex = gradio.Label(num_top_classes=5, label="Model Prediction")
         
         gradio.Examples(
             examples=example_rows_val, 
@@ -151,7 +152,7 @@ with gradio.Blocks(css=custom_css) as demo:
             with gradio.Column():
                 input_img_ex = gradio.Image(label="Selected Test Image", height=512, width=512)
                 truth_box = gradio.Textbox(label="Ground Truth Label", interactive=False)
-            output_lbl_ex = gradio.Label(num_top_classes=3, label="Model Prediction")
+            output_lbl_ex = gradio.Label(num_top_classes=5, label="Model Prediction")
         
         gradio.Examples(
             examples=example_rows_test,