File size: 1,191 Bytes
28bd1c3 dafc309 28bd1c3 14074c9 94b6d80 28bd1c3 dafc309 28bd1c3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | import gradio as gr
from fastai.vision.all import *
from huggingface_hub import from_pretrained_fastai
import torch, os
import traceback
os.environ.setdefault("OMP_NUM_THREADS", "1")
torch.set_num_threads(1)
learn = from_pretrained_fastai("Pablogps/kedar-200-birds")
try:
learn.to_fp32()
except:
pass
labels = learn.dls.vocab
def predict(img):
try:
# img = PILImage.create(img)
pred, pred_idx, probs = learn.predict(img)
return {labels[i]: float(probs[i]) for i in range(len(labels))}
except Exception as e:
tb = traceback.format_exc()
print(tb, flush=True)
raise gr.Error(f"{type(e).__name__}: {e}")
title = "Bird classifier"
description = "A small model that classifies birds, trained quickly with kedar 200."
examples = ['examples_american_crow.jpg', 'examples_barn_swallow.jpg', 'examples_pied_kingfisher.jpg']
demo = gr.Interface(
fn=predict,
inputs=gr.Image(type="pil"),
outputs=gr.Label(num_top_classes=3),
title=title,
description=description,
examples=examples,
cache_examples=False, # <-- don’t pre-run at startup
)
demo.queue(max_size=8).launch(show_error=True, debug=True) |