Post-refactor fixes vol. 2

* Reload model before generation, if it is offloaded to CPU
* Load model if boost got selected
* Do not try to offload pix2pix
* Net dimensions are multiple of 32 regardless of match size
* Change the default net size to default net size of the default model

Author: semjonsona

scripts/core.py

@@ -165,7 +165,9 @@ def core_generation_funnel(outpath, inputimages, inputdepthmaps, inputnames, inp
             else:
                 # override net size (size may be different for different images)
                 if match_size:
-                    net_width, net_height = inputimages[count].width, inputimages[count].height
+                    # Round up to a multiple of 32 to avoid potential issues
+                    net_width = (inputimages[count].width + 31) // 32 * 32
+                    net_height = (inputimages[count].height + 31) // 32 * 32
                 raw_prediction, raw_prediction_invert = \
                     model_holder.get_raw_prediction(inputimages[count], net_width, net_height)
 

scripts/interface_webui.py

@@ -49,8 +49,8 @@ def main_ui_panel(is_depth_tab):
                 with gr.Group(visible=False) as options_depend_on_boost:
                     inp += 'match_size', gr.Checkbox(label="Match net size to input size", value=False)
             with gr.Row(visible=False) as options_depend_on_match_size:
-                inp += 'net_width', gr.Slider(minimum=64, maximum=2048, step=64, label='Net width', value=512)
-                inp += 'net_height', gr.Slider(minimum=64, maximum=2048, step=64, label='Net height', value=512)
+                inp += 'net_width', gr.Slider(minimum=64, maximum=2048, step=64, label='Net width', value=448)
+                inp += 'net_height', gr.Slider(minimum=64, maximum=2048, step=64, label='Net height', value=448)
 
         with gr.Group():
             with gr.Row():