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app.py

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+#@title Prepare the Concepts Library to be used
+
+import requests
+import os
+import gradio as gr
+import wget
+import torch
+from torch import autocast
+from diffusers import StableDiffusionPipeline
+from huggingface_hub import HfApi
+from transformers import CLIPTextModel, CLIPTokenizer
+from tqdm.notebook import tqdm
+
+api = HfApi()
+models_list = api.list_models(author="sd-concepts-library")
+models = []
+
+pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=True, revision="fp16", torch_dtype=torch.float16).to("cuda")
+
+def load_learned_embed_in_clip(learned_embeds_path, text_encoder, tokenizer, token=None):
+  loaded_learned_embeds = torch.load(learned_embeds_path, map_location="cpu")
+  
+  # separate token and the embeds
+  trained_token = list(loaded_learned_embeds.keys())[0]
+  embeds = loaded_learned_embeds[trained_token]
+
+  # cast to dtype of text_encoder
+  dtype = text_encoder.get_input_embeddings().weight.dtype
+  embeds.to(dtype)
+
+  # add the token in tokenizer
+  token = token if token is not None else trained_token
+  num_added_tokens = tokenizer.add_tokens(token)
+  i = 1
+  while(num_added_tokens == 0):
+    print(f"The tokenizer already contains the token {token}.")
+    token = f"{token[:-1]}-{i}>"
+    print(f"Attempting to add the token {token}.")
+    num_added_tokens = tokenizer.add_tokens(token)
+    i+=1
+  
+  # resize the token embeddings
+  text_encoder.resize_token_embeddings(len(tokenizer))
+  
+  # get the id for the token and assign the embeds
+  token_id = tokenizer.convert_tokens_to_ids(token)
+  text_encoder.get_input_embeddings().weight.data[token_id] = embeds
+  return token
+
+print("Setting up the public library")
+for model in tqdm(models_list):
+  model_content = {}
+  model_id = model.modelId
+  model_content["id"] = model_id
+  embeds_url = f"https://huggingface.co/{model_id}/resolve/main/learned_embeds.bin"
+  os.makedirs(model_id,exist_ok = True)
+  if not os.path.exists(f"{model_id}/learned_embeds.bin"):
+    try:
+      wget.download(embeds_url, out=model_id)
+    except:
+      continue
+  token_identifier = f"https://huggingface.co/{model_id}/raw/main/token_identifier.txt"
+  response = requests.get(token_identifier)
+  token_name = response.text
+  
+  concept_type = f"https://huggingface.co/{model_id}/raw/main/type_of_concept.txt"
+  response = requests.get(concept_type)
+  concept_name = response.text
+  model_content["concept_type"] = concept_name
+  images = []
+  for i in range(4):
+    url = f"https://huggingface.co/{model_id}/resolve/main/concept_images/{i}.jpeg"
+    image_download = requests.get(url)
+    url_code = image_download.status_code
+    if(url_code == 200):
+      file = open(f"{model_id}/{i}.jpeg", "wb") ## Creates the file for image
+      file.write(image_download.content) ## Saves file content
+      file.close()
+      images.append(f"{model_id}/{i}.jpeg")
+  model_content["images"] = images
+
+  learned_token = load_learned_embed_in_clip(f"{model_id}/learned_embeds.bin", pipe.text_encoder, pipe.tokenizer, token_name)
+  model_content["token"] = learned_token
+  models.append(model_content)
+  
+#@title Run the app to navigate around [the Library](https://huggingface.co/sd-concepts-library)
+#@markdown Click the `Running on public URL:` result to run the Gradio app
+
+SELECT_LABEL = "Select concept"
+
+def title_block(title, id):
+  return gr.Markdown(f"### [`{title}`](https://huggingface.co/{id})")
+
+def image_block(image_list, concept_type):
+  return gr.Gallery(
+          label=concept_type, value=image_list, elem_id="gallery"
+          ).style(grid=[2], height="auto")
+
+def checkbox_block():
+  checkbox = gr.Checkbox(label=SELECT_LABEL).style(container=False)
+  return checkbox
+
+def infer(text):
+  with autocast("cuda"):
+        images_list = pipe(
+            [text]*2,
+            num_inference_steps=50,
+            guidance_scale=7.5
+  )
+  output_images = []
+  for i, image in enumerate(images_list["sample"]):
+    output_images.append(image)
+  return output_images
+  
+css = '''
+.gradio-container {font-family: 'IBM Plex Sans', sans-serif}
+#top_title{margin-bottom: .5em}
+#top_title h2{margin-bottom: 0; text-align: center}
+#main_row{flex-wrap: wrap; gap: 1em; max-height: calc(100vh - 16em); overflow-y: scroll; flex-direction: row}
+@media (min-width: 768px){#main_row > div{flex: 1 1 32%; margin-left: 0 !important}}
+.gr-prose code::before, .gr-prose code::after {content: "" !important}
+::-webkit-scrollbar {width: 10px}
+::-webkit-scrollbar-track {background: #f1f1f1}
+::-webkit-scrollbar-thumb {background: #888}
+::-webkit-scrollbar-thumb:hover {background: #555}
+.gr-button {white-space: nowrap}
+.gr-button:focus {
+  border-color: rgb(147 197 253 / var(--tw-border-opacity));
+  outline: none;
+  box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
+  --tw-border-opacity: 1;
+  --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
+  --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
+  --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
+  --tw-ring-opacity: .5;
+}
+#prompt_input{flex: 1 3 auto}
+#prompt_area{margin-bottom: .75em}
+#prompt_area > div:first-child{flex: 1 3 auto}
+'''
+examples = ["a <cat-toy> in <madhubani-art> style", "a mecha robot in <line-art> style", "a piano being played by <bonzi>"]
+with gr.Blocks(css=css) as demo:
+  state = gr.Variable({
+        'selected': -1
+  })
+  state = {}
+  def update_state(i):
+        global checkbox_states
+        if(checkbox_states[i]):
+          checkbox_states[i] = False
+          state[i] = False
+        else:
+          state[i] = True
+          checkbox_states[i] = True
+  gr.HTML('''
+  <div style="text-align: center; max-width: 720px; margin: 0 auto;">
+              <div
+                style="
+                  display: inline-flex;
+                  align-items: center;
+                  gap: 0.8rem;
+                  font-size: 1.75rem;
+                "
+              >
+                <svg
+                  width="0.65em"
+                  height="0.65em"
+                  viewBox="0 0 115 115"
+                  fill="none"
+                  xmlns="http://www.w3.org/2000/svg"
+                >
+                  <rect width="23" height="23" fill="white"></rect>
+                  <rect y="69" width="23" height="23" fill="white"></rect>
+                  <rect x="23" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="23" y="69" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="46" width="23" height="23" fill="white"></rect>
+                  <rect x="46" y="69" width="23" height="23" fill="white"></rect>
+                  <rect x="69" width="23" height="23" fill="black"></rect>
+                  <rect x="69" y="69" width="23" height="23" fill="black"></rect>
+                  <rect x="92" width="23" height="23" fill="#D9D9D9"></rect>
+                  <rect x="92" y="69" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="115" y="46" width="23" height="23" fill="white"></rect>
+                  <rect x="115" y="115" width="23" height="23" fill="white"></rect>
+                  <rect x="115" y="69" width="23" height="23" fill="#D9D9D9"></rect>
+                  <rect x="92" y="46" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="92" y="115" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="92" y="69" width="23" height="23" fill="white"></rect>
+                  <rect x="69" y="46" width="23" height="23" fill="white"></rect>
+                  <rect x="69" y="115" width="23" height="23" fill="white"></rect>
+                  <rect x="69" y="69" width="23" height="23" fill="#D9D9D9"></rect>
+                  <rect x="46" y="46" width="23" height="23" fill="black"></rect>
+                  <rect x="46" y="115" width="23" height="23" fill="black"></rect>
+                  <rect x="46" y="69" width="23" height="23" fill="black"></rect>
+                  <rect x="23" y="46" width="23" height="23" fill="#D9D9D9"></rect>
+                  <rect x="23" y="115" width="23" height="23" fill="#AEAEAE"></rect>
+                  <rect x="23" y="69" width="23" height="23" fill="black"></rect>
+                </svg>
+                <h1 style="font-weight: 900; margin-bottom: 7px;">
+                  Stable Diffusion Conceptualizer
+                </h1>
+              </div>
+              <p style="margin-bottom: 10px; font-size: 94%">
+                Navigate through community created concepts and styles via Stable Diffusion Textual Inversion and pick yours for inference.
+                To train your own concepts and contribute to the library <a style="text-decoration: underline" href="https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_textual_inversion_training.ipynb">check out this notebook</a>.
+              </p>
+            </div>
+  ''')
+  with gr.Row():
+        with gr.Column():
+          gr.Markdown('''
+          ### Textual-Inversion trained [concepts library](https://huggingface.co/sd-concepts-library) navigator
+          ''')
+          with gr.Row(elem_id="main_row"):
+                  image_blocks = []
+                  for i, model in enumerate(models):
+                    with gr.Box().style(border=None):
+                      title_block(model["token"], model["id"])
+                      image_blocks.append(image_block(model["images"], model["concept_type"]))
+        with gr.Box():
+                with gr.Row(elem_id="prompt_area").style(mobile_collapse=False, equal_height=True):
+                    text = gr.Textbox(
+                        label="Enter your prompt", placeholder="Enter your prompt", show_label=False, max_lines=1, elem_id="prompt_input"
+                    ).style(
+                        border=(True, False, True, True),
+                        rounded=(True, False, False, True),
+                        container=False                        
+                    )
+                    btn = gr.Button("Run",elem_id="run_btn").style(
+                        margin=False,
+                        rounded=(False, True, True, False)
+                    )  
+                with gr.Row().style():
+                    infer_outputs = gr.Gallery(show_label=False).style(grid=[2], height="512px")
+                with gr.Row():
+                  gr.HTML("<p style=\"font-size: 85%;margin-top: .75em\">Prompting may not work as you are used to; <code>objects</code> may need the concept added at the end.</p>")
+                with gr.Row():
+                  gr.Examples(examples=examples, fn=infer, inputs=[text], outputs=infer_outputs, cache_examples=False)
+  checkbox_states = {}
+  inputs = [text]
+  btn.click(
+        infer,
+        inputs=inputs,
+        outputs=infer_outputs
+    )
+demo.launch(inline=False, debug=True)