from distutils.command.build import build import streamlit as st # HF spaces at v1.2.0 from demo import load_model,generate,get_dataset,embed,make_meme import streamlit.components.v1 as components import io import os root_dir=os.path.dirname(os.path.abspath(__file__)) build_dir = os.path.join(root_dir, "custom_component/frontend/build") _component_func = components.declare_component("release_butterflies", path=build_dir) def release_butterflies(name, key=None): component_value = _component_func(name=name, key=key, default=0) return component_value st.sidebar.subheader("This butterfly does not exist! ") st.sidebar.image("assets/logo.png", width=200) st.title("ButterflyGAN") @st.experimental_singleton def load_model_intocache(model_name,model_version): # model_name='ceyda/butterfly_512_base' gan = load_model(model_name,model_version) return gan @st.experimental_singleton def load_dataset(): dataset=get_dataset() return dataset @st.experimental_singleton def load_variables():# Don't want to open read files over and over. not sure if it makes a diff st.session_state['latent_walk_code']=open("assets/code_snippets/latent_walk.py").read() st.session_state['latent_walk_code_music']=open("assets/code_snippets/latent_walk_music.py").read() def img2download(image): imgByteArr = io.BytesIO() image.save(imgByteArr, format="JPEG") imgByteArr = imgByteArr.getvalue() return imgByteArr model_name='ceyda/butterfly_cropped_uniq1K_512' model_version='57d36a15546909557d9f967f47713236c8288838' # model_version=None model=load_model_intocache(model_name,model_version) dataset=load_dataset() load_variables() generate_menu="🦋 Make butterflies" latent_walk_menu="🎧 Take a latent walk" make_meme_menu="🐦 Make a meme" mosaic_menu="👀 See the mosaic" fun_menu="🙌 Release the butterflies" screen = st.sidebar.radio("Pick a destination",[generate_menu,latent_walk_menu,make_meme_menu,mosaic_menu,fun_menu]) if screen == generate_menu: batch_size=4 #generate 4 butterflies col_num=4 def run(): with st.spinner("Generating..."): ims=generate(model,batch_size) st.session_state['ims'] = ims if 'ims' not in st.session_state: st.session_state['ims'] = None run() ims=st.session_state["ims"] st.write("Light-GAN model trained on 1000 butterfly images taken from the Smithsonian Museum collection. \n \ Based on [paper:](https://openreview.net/forum?id=1Fqg133qRaI) *Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis*") runb=st.button("Generate", on_click=run ,help="generated on the fly maybe slow") if ims is not None: cols=st.columns(col_num) picks=[False]*batch_size for j,im in enumerate(ims): i=j%col_num cols[i].image(im) picks[j]=cols[i].button("Find Nearest",key="pick_"+str(j)) if any(picks): # st.write("Nearest butterflies:") for i,pick in enumerate(picks): if pick: scores, retrieved_examples=dataset.get_nearest_examples('beit_embeddings', embed(ims[i]), k=5) for r in retrieved_examples["image"]: cols[i].image(r) st.write("Nearest neighbors found in the training set according to L2 distance on 'microsoft/beit-base-patch16-224' embeddings") st.write(f"Latent dimension: {model.latent_dim}, image size:{model.image_size}") elif screen == latent_walk_menu: latent_walk_code=open("assets/code_snippets/latent_walk.py").read() latent_walk_music_code=open("assets/code_snippets/latent_walk_music.py").read() st.write("Take a latent walk :musical_note: with cute butterflies") cols=st.columns(3) cols[0].caption("A regular walk (no music)") cols[0].video("assets/latent_walks/regular_walk.mp4") cols[1].caption("Walk with music :butterfly:") cols[1].video("assets/latent_walks/walk_happyrock.mp4") cols[2].caption("Walk with music :butterfly:") cols[2].video("assets/latent_walks/walk_cute.mp4") st.caption("Royalty Free Music from Bensound") st.write("🎧Did those butterflies seem to be dancing to the music?!Here is the secret:") with st.expander("See the Code Snippets"): st.write("A regular latent walk:") st.code(st.session_state['latent_walk_code'], language='python') st.write(":musical_note: latent walk with music:") st.code(st.session_state['latent_walk_code_music'], language='python') elif screen == make_meme_menu: if "pigeon" not in st.session_state: st.session_state['pigeon'] = generate(model,1)[0] def get_pigeon(): st.session_state['pigeon'] = generate(model,1)[0] cols= st.columns(2) cols[0].button("change pigeon",on_click=get_pigeon) no_bg=cols[1].checkbox("Remove background?",True,help="Remove the background from pigeon") show_text=cols[1].checkbox("Show text?",True) meme_text=st.text_input("Enter text","Is this a pigeon?") meme=make_meme(st.session_state['pigeon'],text=meme_text,show_text=show_text,remove_background=no_bg) st.image(meme) coly=st.columns(2) coly[0].download_button("Download", img2download(meme),mime="image/jpeg") coly[1].write("Made a cool one? [Share](https://twitter.com/intent/tweet?text=Check%20out%20the%20demo%20for%20Butterfly%20GAN%20%F0%9F%A6%8Bhttps%3A//huggingface.co/spaces/huggan/butterfly-gan%0Amade%20by%20%40ceyda_cinarel%20%26%20%40johnowhitaker%20) on Twitter") elif screen == mosaic_menu: cols=st.columns(2) cols[0].markdown("These are all the butterflies in our [training set](https://huggingface.co/huggan/smithsonian_butterflies_subset)") cols[0].image("assets/train_data_mosaic_lowres.jpg") cols[0].write("🔎 view the high-res version [here](https://www.easyzoom.com/imageaccess/0c77e0e716f14ea7bc235447e5a4c397)") cols[1].markdown("These are the butterflies our model generated.") cols[1].image("assets/gen_mosaic_lowres.jpg") cols[1].write("🔎 view the high-res version [here](https://www.easyzoom.com/imageaccess/cbb04e81106c4c54a9d9f9dbfb236eab)") elif screen == fun_menu: cols=st.columns([1,2]) cols[0].write("While working on this project") cols[0].image("assets/butterflies_everywhere.jpg") with cols[1]: release_butterflies("Hello World") # footer stuff st.sidebar.caption(f"[Model](https://huggingface.co/ceyda/butterfly_cropped_uniq1K_512) & [Dataset](https://huggingface.co/huggan/smithsonian_butterflies_subset) used") # Link project repo( scripts etc ) # Credits st.sidebar.caption(f"Made during the [huggan](https://github.com/huggingface/community-events) hackathon") st.sidebar.caption(f"Contributors:") st.sidebar.caption(f"[Ceyda Cinarel](https://github.com/cceyda) & [Jonathan Whitaker](https://datasciencecastnet.home.blog/)") ## Feel free to add more & change stuff ^