Commit

app.py

@@ -29,7 +29,7 @@ MAX_IMAGE_SIZE = 2048  # not used anymore
 
 
 @spaces.GPU()
-def infer(prompt, seed=42, randomize_seed=False, aspect_ratio="4:3 landscape 1152x896", lora_weight="lora_weight_rank_32_alpha_32.safetensors",
+def infer(prompt, seed=42, randomize_seed=True, aspect_ratio="4:3 landscape 1152x896", lora_weight="lora_weight_rank_32_alpha_32.safetensors",
           guidance_scale=3.5, num_inference_steps=28, progress=gr.Progress(track_tqdm=True)):
 
     # Randomize seed if requested
@@ -94,7 +94,7 @@ with gr.Blocks(css=css) as demo:
         
         result = gr.Image(label="Result", show_label=False)
         
-        with gr.Accordion("Advanced Settings", open=False):
+        with gr.Accordion("Advanced Settings", open=True):
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,

python.py

@@ -154,8 +154,8 @@ unetloader_12 = unetloader.load_unet(
 ksamplerselect = NODE_CLASS_MAPPINGS["KSamplerSelect"]()
 ksamplerselect_16 = ksamplerselect.get_sampler(sampler_name="dpmpp_2m")
 
-randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
-randomnoise_25 = randomnoise.get_noise(noise_seed='42')
+# randomnoise = NODE_CLASS_MAPPINGS["RandomNoise"]()
+# randomnoise_25 = randomnoise.get_noise(noise_seed='42')
 
 loraloadermodelonly = NODE_CLASS_MAPPINGS["LoraLoaderModelOnly"]()
 loraloadermodelonly_72 = loraloadermodelonly.load_lora_model_only(