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README.md

@@ -1,6 +1,6 @@
 ---
 title: 🧩 DiffuseCraft Mod
-emoji: 🧩🖼️
+emoji: 🧩🖼️📦
 colorFrom: red
 colorTo: pink
 sdk: gradio

app.py

@@ -1,6 +1,3 @@
-#######################
-# UTILS
-#######################
 import spaces
 import os
 from stablepy import Model_Diffusers
@@ -25,6 +22,7 @@ from stablepy import (
     SD15_TASKS,
     SDXL_TASKS,
 )
+import urllib.parse
 
 preprocessor_controlnet = {
   "openpose": [
@@ -59,7 +57,7 @@ preprocessor_controlnet = {
   "lineart": [
     "Lineart",
     "Lineart coarse",
-    "LineartAnime",
+    "Lineart (anime)",
     "None",
     "None (anime)",
   ],
@@ -96,7 +94,7 @@ task_stablepy = {
     'depth ControlNet': 'depth',
     'normalbae ControlNet': 'normalbae',
     'lineart ControlNet': 'lineart',
-    'lineart_anime ControlNet': 'lineart_anime',
+    # 'lineart_anime ControlNet': 'lineart_anime',
     'shuffle ControlNet': 'shuffle',
     'ip2p ControlNet': 'ip2p',
     'optical pattern ControlNet': 'pattern',
@@ -108,7 +106,7 @@ task_model_list = list(task_stablepy.keys())
 
 def download_things(directory, url, hf_token="", civitai_api_key=""):
     url = url.strip()
-
+    
     if "drive.google.com" in url:
         original_dir = os.getcwd()
         os.chdir(directory)
@@ -116,6 +114,7 @@ def download_things(directory, url, hf_token="", civitai_api_key=""):
         os.chdir(original_dir)
     elif "huggingface.co" in url:
         url = url.replace("?download=true", "")
+        # url = urllib.parse.quote(url, safe=':/')  # fix encoding
         if "/blob/" in url:
             url = url.replace("/blob/", "/resolve/")
         user_header = f'"Authorization: Bearer {hf_token}"'
@@ -168,6 +167,7 @@ os.makedirs(directory_loras, exist_ok=True)
 directory_vaes = 'vaes'
 os.makedirs(directory_vaes, exist_ok=True)
 
+
 ## BEGIN MOD
 # - **Download SD 1.5 Models**
 #download_model = "https://huggingface.co/frankjoshua/toonyou_beta6/resolve/main/toonyou_beta6.safetensors"
@@ -215,7 +215,45 @@ def get_model_id_list():
 
     return model_ids
 
-load_diffusers_format_model = get_model_id_list()
+load_diffusers_format_model = [
+    'stabilityai/stable-diffusion-xl-base-1.0',
+    'cagliostrolab/animagine-xl-3.1',
+    'misri/epicrealismXL_v7FinalDestination',
+    'misri/juggernautXL_juggernautX',
+    'misri/zavychromaxl_v80',
+    'SG161222/RealVisXL_V4.0',
+    'misri/newrealityxlAllInOne_Newreality40',
+    'eienmojiki/Anything-XL',
+    'eienmojiki/Starry-XL-v5.2',
+    'gsdf/CounterfeitXL',
+    'kitty7779/ponyDiffusionV6XL',
+    'John6666/ebara-mfcg-pony-mix-v12-sdxl',
+    'John6666/t-ponynai3-v51-sdxl',
+    'yodayo-ai/kivotos-xl-2.0',
+    'yodayo-ai/holodayo-xl-2.1',
+    'digiplay/majicMIX_sombre_v2',
+    'digiplay/majicMIX_realistic_v6',
+    'digiplay/majicMIX_realistic_v7',
+    'digiplay/DreamShaper_8',
+    'digiplay/BeautifulArt_v1',
+    'digiplay/DarkSushi2.5D_v1',
+    'digiplay/darkphoenix3D_v1.1',
+    'digiplay/BeenYouLiteL11_diffusers',
+    'rubbrband/revAnimated_v2Rebirth',
+    'youknownothing/cyberrealistic_v50',
+    'votepurchase/counterfeitV30_v30',
+    'Meina/MeinaMix_V11',
+    'Meina/MeinaUnreal_V5',
+    'Meina/MeinaPastel_V7',
+    'rubbrband/realcartoon3d_v16',
+    'rubbrband/realcartoonRealistic_v14',
+    'KBlueLeaf/Kohaku-XL-Epsilon-rev3',
+]
+
+def list_uniq(l):
+        return sorted(set(l), key=l.index)
+
+load_diffusers_format_model = list_uniq(get_model_id_list() + load_diffusers_format_model)
 ## END MOD
 
 CIVITAI_API_KEY = os.environ.get("CIVITAI_API_KEY")
@@ -254,6 +292,25 @@ lora_model_list.insert(0, "None")
 vae_model_list = get_model_list(directory_vaes)
 vae_model_list.insert(0, "None")
 
+def get_my_lora(link_url):
+    for url in [url.strip() for url in link_url.split(',')]:
+        if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
+            download_things(directory_loras, url, hf_token, CIVITAI_API_KEY)
+    new_lora_model_list = get_model_list(directory_loras)
+    new_lora_model_list.insert(0, "None")
+    
+    return gr.update(
+        choices=new_lora_model_list
+    ), gr.update(
+        choices=new_lora_model_list
+    ), gr.update(
+        choices=new_lora_model_list
+    ), gr.update(
+        choices=new_lora_model_list
+    ), gr.update(
+        choices=new_lora_model_list
+    ),
+
 print('\033[33m🏁 Download and listing of valid models completed.\033[0m')
 
 upscaler_dict_gui = {
@@ -337,6 +394,7 @@ warnings.filterwarnings(action="ignore", category=FutureWarning, module="transfo
 from stablepy import logger
 logger.setLevel(logging.DEBUG)
 
+
 ## BEGIN MOD
 from v2 import (
     V2UI,
@@ -371,6 +429,17 @@ def description_ui():
 ## END MOD
 
 
+def info_html(json_data, title, subtitle):
+    return f"""
+        <div style='padding: 0; border-radius: 10px;'>
+            <p style='margin: 0; font-weight: bold;'>{title}</p>
+            <details>
+                <summary>Details</summary>
+                <p style='margin: 0; font-weight: bold;'>{subtitle}</p>
+            </details>
+        </div>
+        """
+
 class GuiSD:
     def __init__(self, stream=True):
         self.model = None
@@ -384,18 +453,12 @@ class GuiSD:
             retain_task_model_in_cache=False,
         )
 
-    @spaces.GPU(duration=120)
-    def infer(self, model, pipe_params):
-        images, image_list = model(**pipe_params)
-        return images
-
     def load_new_model(self, model_name, vae_model, task, progress=gr.Progress(track_tqdm=True)):
 
         yield f"Loading model: {model_name}"
         
         vae_model = vae_model if vae_model != "None" else None
 
-
         if model_name in model_list:
             model_is_xl = "xl" in model_name.lower()
             sdxl_in_vae = vae_model and "sdxl" in vae_model.lower()
@@ -405,6 +468,7 @@ class GuiSD:
             if incompatible_vae:
                 vae_model = None
 
+        
         self.model.load_pipe(
             model_name,
             task_name=task_stablepy[task],
@@ -412,7 +476,7 @@ class GuiSD:
             type_model_precision=torch.float16,
             retain_task_model_in_cache=False,
         )
-        yield f"Model loaded: {model_name} {vae_model if vae_model else ''}"
+        yield f"Model loaded: {model_name}"
         
     @spaces.GPU
     def generate_pipeline(
@@ -518,15 +582,14 @@ class GuiSD:
         model_ip2,
         mode_ip2,
         scale_ip2,
-        # progress=gr.Progress(track_tqdm=True),
-        # progress=gr.Progress()
     ):
-
-        # progress(0.01, desc="Loading model...")
         
         vae_model = vae_model if vae_model != "None" else None
         loras_list = [lora1, lora2, lora3, lora4, lora5]
+        vae_msg = f"VAE: {vae_model}" if vae_model else ""
+        msg_lora = []
 
+        
         if model_name in model_list:
             model_is_xl = "xl" in model_name.lower()
             sdxl_in_vae = vae_model and "sdxl" in vae_model.lower()
@@ -534,19 +597,23 @@ class GuiSD:
             incompatible_vae = (model_is_xl and vae_model and not sdxl_in_vae) or (not model_is_xl and sdxl_in_vae)
 
             if incompatible_vae:
-                gr.Info(
+                msg_inc_vae = (
                     f"The selected VAE is for a { 'SD 1.5' if model_is_xl else 'SDXL' } model, but you"
                     f" are using a { model_type } model. The default VAE "
                     "will be used."
                 )
+                gr.Info(msg_inc_vae)
+                vae_msg = msg_inc_vae
                 vae_model = None
 
             for la in loras_list:
-                if la is not None and la != "None":
+                if la is not None and la != "None" and la in lora_model_list:
                     print(la)
                     lora_type = ("animetarot" in la.lower() or "Hyper-SD15-8steps".lower() in la.lower())
                     if (model_is_xl and lora_type) or (not model_is_xl and not lora_type):
-                        gr.Info(f"The LoRA {la} is for { 'SD 1.5' if model_is_xl else 'SDXL' }, but you are using { model_type }.")
+                        msg_inc_lora = f"The LoRA {la} is for { 'SD 1.5' if model_is_xl else 'SDXL' }, but you are using { model_type }."
+                        gr.Info(msg_inc_lora)
+                        msg_lora.append(msg_inc_lora)
 
         task = task_stablepy[task]
 
@@ -731,22 +798,27 @@ class GuiSD:
                 pipe_params["num_images"] = num_images
                 gr.Info("Num images x 2 🎉")
 
-        # print("Inference 1")
-        # yield self.infer_short(self.model, pipe_params)
+        # Maybe fix lora issue: 'Cannot copy out of meta tensor; no data!''
+        self.model.pipe.to("cuda:0" if torch.cuda.is_available() else "cpu")
+
+        info_state = f"PROCESSING "
         for img, seed, data in self.model(**pipe_params):
-            info_state = f"PROCESSING..."
+            info_state += ">"
             if data:
-                info_state = f"COMPLETE: seeds={str(seed)}"
+                info_state = f"COMPLETED. Seeds: {str(seed)}"
+                if vae_msg:
+                    info_state = info_state + "<br>" + vae_msg
+                if msg_lora:
+                    info_state = info_state + "<br>" + "<br>".join(msg_lora)
             yield img, info_state
 
 
 sd_gen = GuiSD()
 
 CSS ="""
-#main { width: 100%; }
 .contain { display: flex; flex-direction: column; }
 #component-0 { height: 100%; }
-#gallery { flex-grow: 2; }
+#gallery { flex-grow: 1; }
 """
 sdxl_task = [k for k, v in task_stablepy.items() if v in SDXL_TASKS ]
 sd_task = [k for k, v in task_stablepy.items() if v in SD15_TASKS ]
@@ -780,7 +852,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                 with gr.Accordion("Model and Task", open=False):
                     task_gui = gr.Dropdown(label="Task", choices=sdxl_task, value=task_model_list[0])
                     model_name_gui = gr.Dropdown(label="Model", choices=model_list, value="votepurchase/animagine-xl-3.1", allow_custom_value=True)
-                    optimization_gui = gr.Radio(label="Optimization for SDXL", choices=["None", "Default", "SPO", "DPO", "DPO Turbo", "PCM 16step", "PCM 8step"], value="None", interactive=True)
+                    optimization_gui = gr.Radio(label="Optimization for SDXL", choices=["None", "Default", "SPO", "DPO", "DPO Turbo", "Hyper-SDXL", "PCM 16step", "PCM 8step"], value="None", interactive=True)
                 with gr.Accordion("Generate prompt from Image", open=False):
                     input_image_gui = gr.Image(label="Input image", type="pil", sources=["upload", "clipboard"], height=256)
                     with gr.Accordion(label="Advanced options", open=False):
@@ -936,7 +1008,9 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
 ## END MOD
 
                 with gr.Accordion("Hires fix", open=False, visible=True):
+
                     upscaler_keys = list(upscaler_dict_gui.keys())
+
                     upscaler_model_path_gui = gr.Dropdown(label="Upscaler", choices=upscaler_keys, value=upscaler_keys[0])
                     upscaler_increases_size_gui = gr.Slider(minimum=1.1, maximum=6., step=0.1, value=1.4, label="Upscale by")
                     esrgan_tile_gui = gr.Slider(minimum=0, value=100, maximum=500, step=1, label="ESRGAN Tile")
@@ -946,6 +1020,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     hires_sampler_gui = gr.Dropdown(label="Hires Sampler", choices=["Use same sampler"] + scheduler_names[:-1], value="Use same sampler")
                     hires_prompt_gui = gr.Textbox(label="Hires Prompt", placeholder="Main prompt will be use", lines=3)
                     hires_negative_prompt_gui = gr.Textbox(label="Hires Negative Prompt", placeholder="Main negative prompt will be use", lines=3)
+
                 with gr.Accordion("LoRA", open=False, visible=True):
                     lora1_gui = gr.Dropdown(label="Lora1", choices=lora_model_list)
                     lora_scale_1_gui = gr.Slider(minimum=-2, maximum=2, step=0.01, value=0.33, label="Lora Scale 1")
@@ -957,9 +1032,21 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     lora_scale_4_gui = gr.Slider(minimum=-2, maximum=2, step=0.01, value=0.33, label="Lora Scale 4")
                     lora5_gui = gr.Dropdown(label="Lora5", choices=lora_model_list)
                     lora_scale_5_gui = gr.Slider(minimum=-2, maximum=2, step=0.01, value=0.33, label="Lora Scale 5")
+
+                    with gr.Accordion("From URL", open=False, visible=True):
+                        text_lora = gr.Textbox(label="URL", placeholder="http://...my_lora_url.safetensors", lines=1)
+                        button_lora = gr.Button("Get and update lists of LoRAs")
+                        button_lora.click(
+                            get_my_lora,
+                            [text_lora],
+                            [lora1_gui, lora2_gui, lora3_gui, lora4_gui, lora5_gui]
+                        )
+
                 with gr.Accordion("IP-Adapter", open=False, visible=True):##############
+
                     IP_MODELS = sorted(list(set(IP_ADAPTERS_SD + IP_ADAPTERS_SDXL)))
                     MODE_IP_OPTIONS = ["original", "style", "layout", "style+layout"]
+
                     with gr.Accordion("IP-Adapter 1", open=False, visible=True):
                         image_ip1 = gr.Image(label="IP Image", type="filepath")
                         mask_ip1 = gr.Image(label="IP Mask", type="filepath")
@@ -972,6 +1059,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                         model_ip2 = gr.Dropdown(value="base", label="Model", choices=IP_MODELS)
                         mode_ip2 = gr.Dropdown(value="style", label="Mode", choices=MODE_IP_OPTIONS)
                         scale_ip2 = gr.Slider(minimum=0., maximum=2., step=0.01, value=0.7, label="Scale")
+
                 with gr.Accordion("ControlNet / Img2img / Inpaint", open=False, visible=True):
                     image_control = gr.Image(label="Image ControlNet/Inpaint/Img2img", type="filepath")
                     image_mask_gui = gr.Image(label="Image Mask", type="filepath")
@@ -981,6 +1069,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     )
                     image_resolution_gui = gr.Slider(minimum=64, maximum=2048, step=64, value=1024, label="Image Resolution")
                     preprocessor_name_gui = gr.Dropdown(label="Preprocessor Name", choices=preprocessor_controlnet["canny"])
+
                     def change_preprocessor_choices(task):
                         task = task_stablepy[task]
                         if task in preprocessor_controlnet.keys():
@@ -988,6 +1077,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                         else:
                             choices_task = preprocessor_controlnet["canny"]
                         return gr.update(choices=choices_task, value=choices_task[0])
+
                     task_gui.change(
                         change_preprocessor_choices,
                         [task_gui],
@@ -1001,15 +1091,19 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     control_net_output_scaling_gui = gr.Slider(minimum=0, maximum=5.0, step=0.1, value=1, label="ControlNet Output Scaling in UNet")
                     control_net_start_threshold_gui = gr.Slider(minimum=0, maximum=1, step=0.01, value=0, label="ControlNet Start Threshold (%)")
                     control_net_stop_threshold_gui = gr.Slider(minimum=0, maximum=1, step=0.01, value=1, label="ControlNet Stop Threshold (%)")
+
                 with gr.Accordion("T2I adapter", open=False, visible=True):
                     t2i_adapter_preprocessor_gui = gr.Checkbox(value=True, label="T2i Adapter Preprocessor")
                     adapter_conditioning_scale_gui = gr.Slider(minimum=0, maximum=5., step=0.1, value=1, label="Adapter Conditioning Scale")
                     adapter_conditioning_factor_gui = gr.Slider(minimum=0, maximum=1., step=0.01, value=0.55, label="Adapter Conditioning Factor (%)")
+
                 with gr.Accordion("Styles", open=False, visible=True):
+
                     try:
                         style_names_found = sd_gen.model.STYLE_NAMES
                     except:
                         style_names_found = STYLE_NAMES
+
                     style_prompt_gui = gr.Dropdown(
                         style_names_found,
                         multiselect=True,
@@ -1019,24 +1113,33 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     )
                     style_json_gui = gr.File(label="Style JSON File")
                     style_button = gr.Button("Load styles")
+
                     def load_json_style_file(json):
                         if not sd_gen.model:
                             gr.Info("First load the model")
                             return gr.update(value=None, choices=STYLE_NAMES)
+
                         sd_gen.model.load_style_file(json)
                         gr.Info(f"{len(sd_gen.model.STYLE_NAMES)} styles loaded")
                         return gr.update(value=None, choices=sd_gen.model.STYLE_NAMES)
+
                     style_button.click(load_json_style_file, [style_json_gui], [style_prompt_gui])                        
+
                 with gr.Accordion("Textual inversion", open=False, visible=False):
                     active_textual_inversion_gui = gr.Checkbox(value=False, label="Active Textual Inversion in prompt")
+
                 with gr.Accordion("Detailfix", open=False, visible=True):
+
                     # Adetailer Inpaint Only
                     adetailer_inpaint_only_gui = gr.Checkbox(label="Inpaint only", value=True)
+
                     # Adetailer Verbose
                     adetailer_verbose_gui = gr.Checkbox(label="Verbose", value=False)
+
                     # Adetailer Sampler
                     adetailer_sampler_options = ["Use same sampler"] + scheduler_names[:-1]
                     adetailer_sampler_gui = gr.Dropdown(label="Adetailer sampler:", choices=adetailer_sampler_options, value="Use same sampler")
+
                     with gr.Accordion("Detailfix A", open=False, visible=True):
                         # Adetailer A
                         adetailer_active_a_gui = gr.Checkbox(label="Enable Adetailer A", value=False)
@@ -1049,6 +1152,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                         mask_dilation_a_gui = gr.Number(label="Mask dilation:", value=4, minimum=1)
                         mask_blur_a_gui = gr.Number(label="Mask blur:", value=4, minimum=1)
                         mask_padding_a_gui = gr.Number(label="Mask padding:", value=32, minimum=1)
+
                     with gr.Accordion("Detailfix B", open=False, visible=True):
                         # Adetailer B
                         adetailer_active_b_gui = gr.Checkbox(label="Enable Adetailer B", value=False)
@@ -1061,11 +1165,13 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                         mask_dilation_b_gui = gr.Number(label="Mask dilation:", value=4, minimum=1)
                         mask_blur_b_gui = gr.Number(label="Mask blur:", value=4, minimum=1)
                         mask_padding_b_gui = gr.Number(label="Mask padding:", value=32, minimum=1)
+
                 with gr.Accordion("Other settings", open=False, visible=True):
                     image_previews_gui = gr.Checkbox(value=True, label="Image Previews")
                     hires_before_adetailer_gui = gr.Checkbox(value=False, label="Hires Before Adetailer")
                     hires_after_adetailer_gui = gr.Checkbox(value=True, label="Hires After Adetailer")
                     generator_in_cpu_gui = gr.Checkbox(value=False, label="Generator in CPU")
+
                 with gr.Accordion("More settings", open=False, visible=False):
                     loop_generation_gui = gr.Slider(minimum=1, value=1, label="Loop Generation")
                     retain_task_cache_gui = gr.Checkbox(value=False, label="Retain task model in cache")
@@ -1080,7 +1186,7 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                     xformers_memory_efficient_attention_gui = gr.Checkbox(value=False, label="Xformers Memory Efficient Attention")
 
 ## BEGIN MOD
-                with gr.Accordion("Examples", open=True, visible=True):
+                with gr.Accordion("Examples and help", open=True, visible=True):
                     gr.Examples(
                         examples=[
                             [
@@ -1337,6 +1443,8 @@ with gr.Blocks(theme="NoCrypt/miku", elem_id="main", css=CSS) as app:
                 return 28, 7., 'Euler a', True, 'loras/sdxl-DPO-LoRA.safetensors', 1.
             elif opt == 'DPO Turbo':
                 return 8, 2.5, 'LCM', True, 'loras/sd_xl_dpo_turbo_lora_v1-128dim.safetensors', 1.
+            elif opt == 'Hyper-SDXL':
+                return 12, 6., 'Euler a', True, 'loras/Hyper-SDXL-12steps-CFG-lora.safetensors', 1.
             elif opt == 'Default':
                 return 28, 7., 'Euler a', False, None, 1.
             else: # None