Update UI code

dreambooth_gui.py

@@ -244,6 +244,27 @@ def train_model(
                 f"{output_dir}/last.yaml",
             )
 
+    if pretrained_model_name_or_path == "":
+        msgbox("Source model information is missing")
+        return
+
+    if train_data_dir == "":
+        msgbox("Image folder path is missing")
+        return
+
+    if not os.path.exists(train_data_dir):
+        msgbox("Image folder does not exist")
+        return
+
+    if reg_data_dir != "":
+        if not os.path.exists(reg_data_dir):
+            msgbox("Regularisation folder does not exist")
+            return
+
+    if output_dir == "":
+        msgbox("Output folder path is missing")
+        return
+
     # Get a list of all subfolders in train_data_dir
     subfolders = [
         f for f in os.listdir(train_data_dir)
@@ -701,7 +722,7 @@ with interface:
         with gr.Row():
             seed_input = gr.Textbox(label="Seed", value=1234)
             max_resolution_input = gr.Textbox(label="Max resolution",
-                                              value="512,512")
+                                              value="512,512", placeholder="512,512")
         with gr.Row():
             caption_extention_input = gr.Textbox(
                 label="Caption Extension",
@@ -715,26 +736,27 @@ with interface:
                 step=1,
                 label="Stop text encoder training",
             )
-        with gr.Row():
-            use_safetensors_input = gr.Checkbox(
-                label="Use safetensor when saving", value=False)
-            enable_bucket_input = gr.Checkbox(label="Enable buckets",
-                                              value=True)
-            cache_latent_input = gr.Checkbox(label="Cache latent", value=True)
-            gradient_checkpointing_input = gr.Checkbox(
-                label="Gradient checkpointing", value=False)
         with gr.Row():
             full_fp16_input = gr.Checkbox(
                 label="Full fp16 training (experimental)", value=False)
             no_token_padding_input = gr.Checkbox(label="No token padding",
                                                  value=False)
+            use_safetensors_input = gr.Checkbox(
+                label="Use safetensor when saving", value=False)
+
+            gradient_checkpointing_input = gr.Checkbox(
+                label="Gradient checkpointing", value=False)
+        with gr.Row():
+            enable_bucket_input = gr.Checkbox(label="Enable buckets",
+                                              value=True)
+            cache_latent_input = gr.Checkbox(label="Cache latent", value=True)
             use_8bit_adam_input = gr.Checkbox(label="Use 8bit adam",
                                               value=True)
             xformers_input = gr.Checkbox(label="Use xformers", value=True)
 
     with gr.Tab("Model conversion"):
         convert_to_safetensors_input = gr.Checkbox(
-            label="Convert to SafeTensors", value=False)
+            label="Convert to SafeTensors", value=True)
         convert_to_ckpt_input = gr.Checkbox(label="Convert to CKPT",
                                             value=False)