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app.py

@@ -1,15 +1,12 @@
-# Thank AK. https://huggingface.co/spaces/akhaliq/cool-japan-diffusion-2-1-0/blob/main/app.py
-from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, EulerAncestralDiscreteScheduler
-from transformers import CLIPFeatureExtractor
+from diffusers import StableDiffusionPipeline, StableDiffusionImg2ImgPipeline, DPMSolverMultistepScheduler
 import gradio as gr
 import torch
 from PIL import Image
 
-model_id = 'aipicasso/cool-japan-diffusion-2-1-0'
+model_id = 'aipicasso/cool-japan-diffusion-2-1-1-beta'
 prefix = ''
-
-scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
-feature_extractor = CLIPFeatureExtractor.from_pretrained(model_id)
+     
+scheduler = DPMSolverMultistepScheduler.from_pretrained(model_id, subfolder="scheduler")
 
 pipe = StableDiffusionPipeline.from_pretrained(
   model_id,
@@ -19,11 +16,7 @@ pipe = StableDiffusionPipeline.from_pretrained(
 pipe_i2i = StableDiffusionImg2ImgPipeline.from_pretrained(
   model_id,
   torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
-  scheduler=scheduler,
-  requires_safety_checker=False,
-  safety_checker=None,
-  feature_extractor=feature_extractor
-)
+  scheduler=scheduler)
 
 if torch.cuda.is_available():
   pipe = pipe.to("cuda")
@@ -33,55 +26,21 @@ def error_str(error, title="Error"):
     return f"""#### {title}
             {error}"""  if error else ""
 
-def inference(prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, neg_prompt="", disable_auto_prompt_correction=False):
+def inference(prompt, guidance, steps, width=512, height=512, seed=0, img=None, strength=0.5, neg_prompt="", auto_prefix=False):
 
   generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None
+  prompt = f"{prefix} {prompt}" if auto_prefix else prompt
 
   try:
     if img is not None:
-      return img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height, generator, disable_auto_prompt_correction), None
+      return img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height, generator), None
     else:
-      return txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator, disable_auto_prompt_correction), None
+      return txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator), None
   except Exception as e:
     return None, error_str(e)
 
-def auto_prompt_correction(prompt_ui,neg_prompt_ui):
-    # auto prompt correction
-    prompt=str(prompt_ui)
-    neg_prompt=str(neg_prompt_ui)
-    prompt=prompt.lower()
-    neg_prompt=neg_prompt.lower()
-    if(prompt=="" and neg_prompt==""):
-        prompt="anime, a portrait of a girl, 4k, detailed"
-        neg_prompt=" (((deformed))), blurry, ((((bad anatomy)))), bad pupil, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), bad hands, fused fingers, messy drawing, broken legs censor, low quality, ((mutated hands and fingers:1.5), (long body :1.3), (mutation, poorly drawn :1.2), ((bad eyes)), ui, error, missing fingers, fused fingers, one hand with more than 5 fingers, one hand with less than 5 fingers, one hand with more than 5 digit, one hand with less than 5 digit, extra digit, fewer digits, fused digit, missing digit, bad digit, liquid digit, long body, uncoordinated body, unnatural body, lowres, jpeg artifacts, 2d, 3d, cg, text"
-
-    splited_prompt=prompt.replace(","," ").replace("_"," ").split(" ")
-    splited_prompt=["girl" if p=="1girl" or p=="solo" else p for p in splited_prompt]
-    splited_prompt=["boy" if p=="1boy" else p for p in splited_prompt]
-    human_words=["girl","maid","female","woman","boy","male","man","guy"]
-    for word in human_words:
-        if( word in splited_prompt):
-            prompt=f"anime, {prompt}, 4k, detailed"
-            neg_prompt=" (((deformed))), blurry, ((((bad anatomy)))), bad pupil, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), bad hands, fused fingers, messy drawing, broken legs censor, low quality, ((mutated hands and fingers:1.5), (long body :1.3), (mutation, poorly drawn :1.2), ((bad eyes)), ui, error, missing fingers, fused fingers, one hand with more than 5 fingers, one hand with less than 5 fingers, one hand with more than 5 digit, one hand with less than 5 digit, extra digit, fewer digits, fused digit, missing digit, bad digit, liquid digit, long body, uncoordinated body, unnatural body, lowres, jpeg artifacts, 2d, 3d, cg, text"
-
-    animal_words=["cat","dog","bird"]
-    for word in animal_words:
-        if( word in splited_prompt):
-            prompt=f"anime, a {word}, 4k, detailed"
-            neg_prompt=" (((deformed))), blurry, ((((bad anatomy)))), bad pupil, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), bad hands, fused fingers, messy drawing, broken legs censor, low quality, ((mutated hands and fingers:1.5), (long body :1.3), (mutation, poorly drawn :1.2), ((bad eyes)), ui, error, missing fingers, fused fingers, one hand with more than 5 fingers, one hand with less than 5 fingers, one hand with more than 5 digit, one hand with less than 5 digit, extra digit, fewer digits, fused digit, missing digit, bad digit, liquid digit, long body, uncoordinated body, unnatural body, lowres, jpeg artifacts, 2d, 3d, cg, text"
-
-    background_words=["mount fuji","mt. fuji","building", "buildings", "tokyo"]
-    for word in background_words:
-        if( word in splited_prompt):
-            prompt=f"anime, shinkai makoto, {word}, 4k, 8k, highly detailed"
-            neg_prompt=" (((deformed))), photo, people, low quality, ui, error, lowres, jpeg artifacts, 2d, 3d, cg, text"
-
-    return prompt,neg_prompt
-    
-def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator,disable_auto_prompt_correction):
-    if(not disable_auto_prompt_correction):
-        prompt,neg_prompt=auto_prompt_correction(prompt,neg_prompt)
-    
+def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator):
+
     result = pipe(
       prompt,
       negative_prompt = neg_prompt,
@@ -93,10 +52,8 @@ def txt_to_img(prompt, neg_prompt, guidance, steps, width, height, generator,dis
     
     return result.images[0]
 
-def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height, generator,disable_auto_prompt_correction):
-    if(not disable_auto_prompt_correction):
-        prompt,neg_prompt=auto_prompt_correction(prompt,neg_prompt)
-        
+def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height, generator):
+
     ratio = min(height / img.height, width / img.width)
     img = img.resize((int(img.width * ratio), int(img.height * ratio)), Image.LANCZOS)
     result = pipe_i2i(
@@ -106,8 +63,8 @@ def img_to_img(prompt, neg_prompt, img, strength, guidance, steps, width, height
         num_inference_steps = int(steps),
         strength = strength,
         guidance_scale = guidance,
-        #width = width,
-        #height = height,
+        width = width,
+        height = height,
         generator = generator)
         
     return result.images[0]
@@ -119,23 +76,14 @@ with gr.Blocks(css=css) as demo:
         f"""
             <div class="main-div">
               <div>
-                <h1>Cool Japan Diffusion 2.1.0</h1>
+                <h1>Cool Japan Diffusion 2 1 1 Beta</h1>
               </div>
               <p>
-               Demo for <a href="https://huggingface.co/aipicasso/cool-japan-diffusion-2-1-0">Cool Japan Diffusion 2 1 0</a> Stable Diffusion model.<br>
+               Demo for <a href="https://huggingface.co/aipicasso/cool-japan-diffusion-2-1-1-beta">Cool Japan Diffusion 2 1 1 Beta</a> Stable Diffusion model.<br>
                {"Add the following tokens to your prompts for the model to work properly: <b>prefix</b>" if prefix else ""}
               </p>
-              <p>
-              sample prompt1 : girl
-              </p>
-              <p>
-              sample prompt2 : boy
-              </p>
-              <p>
-              <a href="https://alfredplpl.hatenablog.com/entry/2022/12/30/102636">日本語の取扱説明書</a>.
-              </p>
-              Running on {"<b>GPU 🔥</b>" if torch.cuda.is_available() else f"<b>CPU 🥶</b>. For faster inference it is recommended to <b>upgrade to GPU in <a href='https://huggingface.co/spaces/akhaliq/cool-japan-diffusion-2-1-0/settings'>Settings</a></b>"} after duplicating the space<br><br>
-              <a style="display:inline-block" href="https://huggingface.co/spaces/akhaliq/cool-japan-diffusion-2-1-0?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
+              Running on {"<b>GPU 🔥</b>" if torch.cuda.is_available() else f"<b>CPU 🥶</b>. For faster inference it is recommended to <b>upgrade to GPU in <a href='https://huggingface.co/spaces/alfredplpl/cool-japan-diffusion-latest-demo/settings'>Settings</a></b>"} after duplicating the space<br><br>
+              <a style="display:inline-block" href="https://huggingface.co/spaces/alfredplpl/cool-japan-diffusion-latest-demo?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
             </div>
         """
     )
@@ -154,11 +102,11 @@ with gr.Blocks(css=css) as demo:
           with gr.Tab("Options"):
             with gr.Group():
               neg_prompt = gr.Textbox(label="Negative prompt", placeholder="What to exclude from the image")
-              disable_auto_prompt_correction = gr.Checkbox(label="Disable auto prompt corretion.")
+              auto_prefix = gr.Checkbox(label="Prefix styling tokens automatically ()", value=prefix, visible=prefix)
 
               with gr.Row():
                 guidance = gr.Slider(label="Guidance scale", value=7.5, maximum=15)
-                steps = gr.Slider(label="Steps", value=20, minimum=2, maximum=75, step=1)
+                steps = gr.Slider(label="Steps", value=25, minimum=2, maximum=75, step=1)
 
               with gr.Row():
                 width = gr.Slider(label="Width", value=512, minimum=64, maximum=1024, step=8)
@@ -171,7 +119,9 @@ with gr.Blocks(css=css) as demo:
                 image = gr.Image(label="Image", height=256, tool="editor", type="pil")
                 strength = gr.Slider(label="Transformation strength", minimum=0, maximum=1, step=0.01, value=0.5)
 
-    inputs = [prompt, guidance, steps, width, height, seed, image, strength, neg_prompt, disable_auto_prompt_correction]
+    auto_prefix.change(lambda x: gr.update(placeholder=f"{prefix} [your prompt]" if x else "[Your prompt]"), inputs=auto_prefix, outputs=prompt, queue=False)
+
+    inputs = [prompt, guidance, steps, width, height, seed, image, strength, neg_prompt, auto_prefix]
     outputs = [image_out, error_output]
     prompt.submit(inference, inputs=inputs, outputs=outputs)
     generate.click(inference, inputs=inputs, outputs=outputs)
@@ -184,4 +134,4 @@ with gr.Blocks(css=css) as demo:
     """)
 
 demo.queue(concurrency_count=1)
-demo.launch()
+demo.launch()