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import gradio as gr |
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from clip_interrogator import Config, Interrogator |
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from share_btn import community_icon_html, loading_icon_html, share_js |
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MODELS = ['ViT-L (best for Stable Diffusion 1.*)'] |
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config = Config(clip_model_name="ViT-L-14/openai") |
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ci_vitl = Interrogator(config) |
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def image_analysis(image, clip_model_name): |
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ci = ci_vitl |
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image = image.convert('RGB') |
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image_features = ci.image_to_features(image) |
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top_mediums = ci.mediums.rank(image_features, 5) |
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top_artists = ci.artists.rank(image_features, 5) |
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top_movements = ci.movements.rank(image_features, 5) |
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top_trendings = ci.trendings.rank(image_features, 5) |
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top_flavors = ci.flavors.rank(image_features, 5) |
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medium_ranks = {medium: sim for medium, sim in zip(top_mediums, ci.similarities(image_features, top_mediums))} |
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artist_ranks = {artist: sim for artist, sim in zip(top_artists, ci.similarities(image_features, top_artists))} |
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movement_ranks = {movement: sim for movement, sim in zip(top_movements, ci.similarities(image_features, top_movements))} |
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trending_ranks = {trending: sim for trending, sim in zip(top_trendings, ci.similarities(image_features, top_trendings))} |
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flavor_ranks = {flavor: sim for flavor, sim in zip(top_flavors, ci.similarities(image_features, top_flavors))} |
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return medium_ranks, artist_ranks, movement_ranks, trending_ranks, flavor_ranks |
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def image_to_prompt(image, clip_model_name, mode): |
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ci = ci_vitl |
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ci.config.blip_num_beams = 64 |
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ci.config.chunk_size = 2048 |
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ci.config.flavor_intermediate_count = 2048 if clip_model_name == MODELS[0] else 1024 |
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image = image.convert('RGB') |
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if mode == 'best': |
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prompt = ci.interrogate(image) |
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elif mode == 'classic': |
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prompt = ci.interrogate_classic(image) |
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elif mode == 'fast': |
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prompt = ci.interrogate_fast(image) |
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elif mode == 'negative': |
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prompt = ci.interrogate_negative(image) |
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return prompt, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) |
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TITLE = """ |
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<div style="text-align: center; max-width: 650px; margin: 0 auto;"> |
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<div |
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style=" |
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display: inline-flex; |
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align-items: center; |
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gap: 0.8rem; |
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font-size: 1.75rem; |
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" |
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> |
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<h1 style="font-weight: 900; margin-bottom: 7px;"> |
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CLIP Interrogator |
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</h1> |
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</div> |
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<p style="margin-bottom: 10px; font-size: 94%"> |
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Want to figure out what a good prompt might be to create new images like an existing one?<br>The CLIP Interrogator is here to get you answers! |
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</p> |
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<p>You can skip the queue by duplicating this space and upgrading to gpu in settings: <a style='display:inline-block' href='https://huggingface.co/spaces/pharmapsychotic/CLIP-Interrogator?duplicate=true'><img src='https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14' alt='Duplicate Space'></a></p> |
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</div> |
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""" |
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ARTICLE = """ |
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<div style="text-align: center; max-width: 650px; margin: 0 auto;"> |
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<p> |
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Example art by <a href="https://pixabay.com/illustrations/watercolour-painting-art-effect-4799014/">Layers</a> |
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and <a href="https://pixabay.com/illustrations/animal-painting-cat-feline-pet-7154059/">Lin Tong</a> |
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from pixabay.com |
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</p> |
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<p> |
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Server busy? You can also run on <a href="https://colab.research.google.com/github/pharmapsychotic/clip-interrogator/blob/main/clip_interrogator.ipynb">Google Colab</a> |
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</p> |
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<p> |
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Has this been helpful to you? Follow me on twitter |
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<a href="https://twitter.com/pharmapsychotic">@pharmapsychotic</a><br> |
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and check out more tools at my |
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<a href="https://pharmapsychotic.com/tools.html">Ai generative art tools list</a> |
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</p> |
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</div> |
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""" |
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CSS = """ |
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#col-container {margin-left: auto; margin-right: auto;} |
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a {text-decoration-line: underline; font-weight: 600;} |
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.animate-spin { |
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animation: spin 1s linear infinite; |
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} |
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@keyframes spin { |
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from { transform: rotate(0deg); } |
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to { transform: rotate(360deg); } |
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} |
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#share-btn-container { |
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display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; |
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} |
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#share-btn { |
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all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; |
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} |
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#share-btn * { |
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all: unset; |
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} |
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#share-btn-container div:nth-child(-n+2){ |
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width: auto !important; |
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min-height: 0px !important; |
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} |
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#share-btn-container .wrap { |
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display: none !important; |
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} |
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""" |
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def analyze_tab(): |
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with gr.Column(): |
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with gr.Row(): |
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image = gr.Image(type='pil', label="Image") |
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model = gr.Dropdown(MODELS, value=MODELS[0], label='CLIP Model') |
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with gr.Row(): |
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medium = gr.Label(label="Medium", num_top_classes=5) |
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artist = gr.Label(label="Artist", num_top_classes=5) |
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movement = gr.Label(label="Movement", num_top_classes=5) |
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trending = gr.Label(label="Trending", num_top_classes=5) |
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flavor = gr.Label(label="Flavor", num_top_classes=5) |
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button = gr.Button("Analyze", api_name="image-analysis") |
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button.click(image_analysis, inputs=[image, model], outputs=[medium, artist, movement, trending, flavor]) |
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examples=[['example01.jpg', MODELS[0]], ['example02.jpg', MODELS[0]]] |
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ex = gr.Examples( |
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examples=examples, |
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fn=image_analysis, |
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inputs=[input_image, input_model], |
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outputs=[medium, artist, movement, trending, flavor], |
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cache_examples=True, |
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run_on_click=True |
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) |
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ex.dataset.headers = [""] |
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with gr.Blocks(css=CSS) as block: |
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with gr.Column(elem_id="col-container"): |
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gr.HTML(TITLE) |
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with gr.Tab("Prompt"): |
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with gr.Row(): |
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input_image = gr.Image(type='pil', elem_id="input-img") |
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with gr.Column(): |
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input_model = gr.Dropdown(MODELS, value=MODELS[0], label='CLIP Model') |
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input_mode = gr.Radio(['best', 'fast', 'classic', 'negative'], value='best', label='Mode') |
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submit_btn = gr.Button("Submit", api_name="image-to-prompt") |
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output_text = gr.Textbox(label="Output", elem_id="output-txt") |
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with gr.Group(elem_id="share-btn-container"): |
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community_icon = gr.HTML(community_icon_html, visible=False) |
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loading_icon = gr.HTML(loading_icon_html, visible=False) |
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share_button = gr.Button("Share to community", elem_id="share-btn", visible=False) |
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examples=[['example01.jpg', MODELS[0], 'best'], ['example02.jpg', MODELS[0], 'best']] |
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ex = gr.Examples( |
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examples=examples, |
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fn=image_to_prompt, |
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inputs=[input_image, input_model, input_mode], |
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outputs=[output_text, share_button, community_icon, loading_icon], |
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cache_examples=True, |
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run_on_click=True |
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) |
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ex.dataset.headers = [""] |
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with gr.Tab("Analyze"): |
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analyze_tab() |
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gr.HTML(ARTICLE) |
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submit_btn.click( |
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fn=image_to_prompt, |
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inputs=[input_image, input_model, input_mode], |
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outputs=[output_text, share_button, community_icon, loading_icon] |
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) |
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share_button.click(None, [], [], _js=share_js) |
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block.queue(max_size=64).launch(show_api=False) |
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