Spaces:
Running
Running
| import pickle | |
| import gradio as gr | |
| from datasets import load_dataset | |
| from transformers import AutoModel, AutoFeatureExtractor | |
| import wikipedia | |
| # Only runs once when the script is first run. | |
| with open("index_768_cosine.pickle", "rb") as handle: | |
| index = pickle.load(handle) | |
| # Load model for computing embeddings. | |
| feature_extractor = AutoFeatureExtractor.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840") | |
| model = AutoModel.from_pretrained("sasha/autotrain-butterfly-similarity-2490576840") | |
| # Candidate images. | |
| dataset = load_dataset("sasha/butterflies_10k_names_multiple") | |
| ds = dataset["train"] | |
| def query(image, top_k=4): | |
| inputs = feature_extractor(image, return_tensors="pt") | |
| model_output = model(**inputs) | |
| embedding = model_output.pooler_output.detach() | |
| results = index.query(embedding, k=top_k) | |
| inx = results[0][0].tolist() | |
| logits = results[1][0].tolist() | |
| images = ds.select(inx)["image"] | |
| captions = ds.select(inx)["name"] | |
| images_with_captions = [(i, c) for i, c in zip(images,captions)] | |
| labels_with_probs = dict(zip(captions,logits)) | |
| labels_with_probs = {k: 1- v for k, v in labels_with_probs.items()} | |
| try: | |
| description = wikipedia.summary(captions[0], sentences = 1) | |
| description = "### " + description | |
| url = wikipedia.page(captions[0]).url | |
| url = " You can learn more about your butterfly [here](" + str(url) + ")!" | |
| description = description + url | |
| except: | |
| description = "### Butterflies are insects in the order Lepidoptera, which also includes moths. Adult butterflies have large, often brightly coloured wings." | |
| url = "https://en.wikipedia.org/wiki/Butterfly" | |
| url = " You can learn more about butterflies [here](" + str(url) + ")!" | |
| description = description + url | |
| return images_with_captions, labels_with_probs, description | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# Find my Butterfly 🦋") | |
| gr.Markdown("## Use this Space to find your butterfly, based on the [iNaturalist butterfly dataset](https://huggingface.co/datasets/huggan/inat_butterflies_top10k)!") | |
| with gr.Row(): | |
| with gr.Column(min_width= 900): | |
| inputs = gr.Image(shape=(800, 1600)) | |
| btn = gr.Button("Find my butterfly!") | |
| description = gr.Markdown() | |
| with gr.Column(): | |
| outputs=gr.Gallery().style(grid=[2], height="auto") | |
| labels = gr.Label() | |
| gr.Markdown("### Image Examples") | |
| gr.Examples( | |
| examples=["elton.jpg", "ken.jpg", "gaga.jpg", "taylor.jpg"], | |
| inputs=inputs, | |
| outputs=[outputs,labels], | |
| fn=query, | |
| cache_examples=True, | |
| ) | |
| btn.click(query, inputs, [outputs, labels, description]) | |
| demo.launch() | |