update image padding for xai

app.py

@@ -289,7 +289,7 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
     with gr.Tab("Specimen Workbench"):
         with gr.Row():
             with gr.Column():
-                original_image = gr.Image(visible = True)
+                original_image = gr.Image(visible = False)
                 workbench_image = gr.Image(label="Workbench Image")
                 classify_image_button = gr.Button("Classify Image")
             

explanations.py

@@ -8,11 +8,14 @@ import numpy as np
 import matplotlib.pyplot as plt
 from inference_resnet import inference_resnet_finer, preprocess, _clever_crop
 from labels import lookup_140
+from app import preprocess_image
 BATCH_SIZE = 1
 
-def show(img, p=False, **kwargs):
+def show(img, p=False,output_size, **kwargs):
     img = np.array(img, dtype=np.float32)
 
+    img = preprocess_image(img, output_size=output_size)
+
     # check if channel first
     if img.shape[0] == 1:
         img = img[0]
@@ -106,8 +109,8 @@ def explain(model, input_image,explain_method,nb_samples,size=600, n_classes=171
             phi = np.abs(explainer(X, Y))[0]
             if len(phi.shape) == 3:
                 phi = np.mean(phi, -1)
-            show(X[0])
-            show(phi, p=1, alpha=0.4)
+            show(X[0],output_size = size)
+            show(phi, p=1, alpha=0.4, output_size = size)
             # show(X[0][:,size_repetitions:2*size_repetitions,:])
             # show(phi[:,size_repetitions:2*size_repetitions], p=1, alpha=0.4)
             plt.savefig(f'phi_{e}{i}.png')