Update app.py

app.py

@@ -18,6 +18,8 @@ import pickle
 from PIL import Image
 import tqdm
 import shutil
+from datetime import datetime
+
 
 wellcomingMessage = """
     <h1>💥 Handwriting Synthesis - Generate text in anyone's handwriting 💥 </h1>
@@ -39,35 +41,46 @@ model.eval()
 def generate_image(text,folder, _ch3, images):
     # Your image generation logic goes here (replace with your actual implementation)
     # For demonstration purposes, we'll just concatenate the uploaded images horizontally.
-    if images:
-      style_inputs, width_length = load_itw_samples(images)
-    elif folder:
-      style_inputs, width_length = load_itw_samples(folder)
-    else:
-      return None
-    # Load images
-    text = text.replace("\n", "").replace("\t", "")
-    text_encode =  [j.encode() for j in text.split(' ')]
-    eval_text_encode, eval_len_text = model.netconverter.encode(text_encode)
-    eval_text_encode = eval_text_encode.to(DEVICE).repeat(batch_size, 1, 1)
-
-    input_styles, page_val = model._generate_page(style_inputs.to(DEVICE).clone(), width_length, eval_text_encode, eval_len_text, no_concat = True)
-    page_val = crop_(page_val[0]*255)
-    input_styles = crop_(input_styles[0]*255)
-
-    max_width = max(page_val.shape[1],input_styles.shape[1])
-
-    if page_val.shape[1]!=max_width:
-      page_val = np.concatenate([page_val, np.ones((page_val.shape[0],max_width-page_val.shape[1]))*255], 1)
-    else:
-      input_styles = np.concatenate([input_styles, np.ones((input_styles.shape[0],max_width-input_styles.shape[1]))*255], 1)
+    try:
+        text_copy = text.copy()
+        if images:
+          style_log = images
+          style_inputs, width_length = load_itw_samples(images)
+        elif folder:
+          style_log = folder
+          style_inputs, width_length = load_itw_samples(folder)
+        else:
+          return None
+        # Load images
+        text = text.replace("\n", "").replace("\t", "")
+        text_encode =  [j.encode() for j in text.split(' ')]
+        eval_text_encode, eval_len_text = model.netconverter.encode(text_encode)
+        eval_text_encode = eval_text_encode.to(DEVICE).repeat(batch_size, 1, 1)
+    
+        input_styles, page_val = model._generate_page(style_inputs.to(DEVICE).clone(), width_length, eval_text_encode, eval_len_text, no_concat = True)
+        page_val = crop_(page_val[0]*255)
+        input_styles = crop_(input_styles[0]*255)
+    
+        max_width = max(page_val.shape[1],input_styles.shape[1])
+    
+        if page_val.shape[1]!=max_width:
+          page_val = np.concatenate([page_val, np.ones((page_val.shape[0],max_width-page_val.shape[1]))*255], 1)
+        else:
+          input_styles = np.concatenate([input_styles, np.ones((input_styles.shape[0],max_width-input_styles.shape[1]))*255], 1)
+        
+        upper_pad = np.ones((45,input_styles.shape[1]))*255
+        input_styles = np.concatenate([upper_pad, input_styles], 0)
+        page_val = np.concatenate([upper_pad, page_val], 0)
     
-    upper_pad = np.ones((45,input_styles.shape[1]))*255
-    input_styles = np.concatenate([upper_pad, input_styles], 0)
-    page_val = np.concatenate([upper_pad, page_val], 0)
+        page_val = Image.fromarray(page_val).convert('RGB')
+        input_styles = Image.fromarray(input_styles).convert('RGB')
+        
+        current_datetime = datetime.now()
+        formatted_datetime = current_datetime.strftime("%Y-%m-%d %H:%M:%S")
 
-    page_val = Image.fromarray(page_val).convert('RGB')
-    input_styles = Image.fromarray(input_styles).convert('RGB')
+        print (f'{formatted_datetime}: input_string - {text_copy}, style_input - {style_log}')
+    except:
+        print ('ERROR! Try again.')
 
     return input_styles, page_val