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import gradio as gr | |
from huggingface_hub import hf_hub_download | |
from fastai.learner import load_learner | |
import os | |
TOKEN = os.environ["token"] | |
REPO_ID = "42digital/deepfashion_classification_vit-large-patch14-clip-336" | |
FILENAME = "model.pkl" | |
learner = load_learner( | |
hf_hub_download(repo_id=REPO_ID, filename=FILENAME, token=TOKEN) | |
) | |
def predict(img): | |
_, _, probs = learner.predict(img) | |
probs = [float(p) for p in probs.detach()] | |
preds = {k: v for k, v in zip(learner.dls.vocab, probs)} | |
return preds | |
gr.Interface(fn=predict, | |
inputs=gr.Image(type="numpy"), | |
outputs=gr.Label(num_top_classes=4), | |
examples=[]).launch() |