Update app.py

app.py

@@ -43,42 +43,21 @@ def generate_docs():
     row_cells[1].text = docs[i][1]
     row_cells[2].text = docs[i][2]
   document.save("casting_report.docx")
-  return [gr.UploadButton(visible=True), gr.DownloadButton(visible=True)]
+  return [gr.UploadButton(visible=True), gr.DownloadButton(visible=True), gr.DownloadButton(label=f"Download", value="casting_report.docx", visible=True)]
 
+def download_file():
+    return [gr.UploadButton(visible=True), gr.DownloadButton(visible=True), gr.DownloadButton(visible=True)]
 
 with gr.Blocks() as demo:
     with gr.Column():
         f = gr.File(file_count="multiple", file_types=[".jpg", ".jpeg", ".png", ".bmp", ".tif", ".tiff"])
         u = gr.Button("Upload files", visible=True)
-        d = gr.DownloadButton("Download report", visible=True)
+        d1 = gr.DownloadButton("Download report", visible=True)
+        d2 = gr.DownloadButton("download report", visible=False)
     r = gr.DataFrame(headers=["Index", "File", "Result"])
 
-    u.click(upload_images, f, [r, u, d])
-    d.click(generate_docs, None, [u, d])
-
-
-"""
-def upload_images(image_paths):
-  df = pd.DataFrame(columns=["Index", "File", "Result"])
-  for i in range(len(image_paths)):
-    df.loc[i] = [str(i+1), image_paths[i].split("\\")[-1], predict(image_paths[i])]
-  return df
-
-# Function to preprocess image and predict
-def predict(image_path):
-  img = keras.utils.load_img(image_path, target_size=(300, 300))
-  img_array = keras.utils.img_to_array(img)
-  img_array = keras.ops.expand_dims(img_array, 0)
-  prediction = model.predict(img_array)
-  class_names = ["Defective", "Normal"]  # Class 0: def, Class 1: ok
-  predicted_class = class_names[1] if prediction > 0.5 else class_names[0]
-  return predicted_class
-
-demo = gr.Interface(
-    upload_images, 
-    gr.File(file_count="multiple", file_types=[".jpg", ".jpeg", ".png", ".bmp", ".tif", ".tiff"]), 
-    gr.DataFrame(headers=["Index", "File", "Result"])
-)
-"""
+    u.click(upload_images, f, [r, u, d1])
+    d1.click(generate_docs, None, [u, d1, d2])
+    d2.click(download_file, None, [u, d1, d2])
 
 demo.launch(share=True, debug=True)