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| # /static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fhow-to-fix-workload-evicted-storage-limit-exceeded-50g-error-in-huggingface-spaces%2F169258%3C%2Fspan%3E%3C!-- HTML_TAG_END --> | |
| import os | |
| import torch | |
| # CRITICAL: Redirect cache to temporary storage | |
| os.environ['TORCH_HOME'] = '/tmp/torch_cache' | |
| os.environ['HUB_DIR'] = '/tmp/torch_hub' | |
| os.environ['TMPDIR'] = '/tmp' | |
| torch.hub.set_dir('/tmp/torch_hub') | |
| import glob | |
| import gradio as gr | |
| from ultralytics import YOLO | |
| model_path = "best.pt" | |
| model = YOLO(model_path) | |
| PREDICT_KWARGS = { | |
| "classes": 0, | |
| "conf": 0.25, | |
| } | |
| def run(image_path): | |
| results = model.predict(image_path, **PREDICT_KWARGS) | |
| return results[0].plot()[:, :, ::-1] # reverse channels for gradio | |
| title = "Megalodon Detector" | |
| description = ( | |
| "" | |
| ) | |
| examples = glob.glob("images/*.png") | |
| interface = gr.Interface( | |
| run, | |
| inputs=[gr.components.Image(type="filepath")], | |
| outputs=gr.components.Image(type="numpy"), | |
| title=title, | |
| description=description, | |
| examples=examples, | |
| ) | |
| interface.queue().launch() | |