ibvhim commited on
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1deb350
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1 Parent(s): 639e2de

Rename onnx_guide/app.py to Image_Classification_EfficientNetLite4/app.py

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- Renamed the sub-folder
- Added an additional image (previous one did not load properly)

{onnx_guide β†’ Image_Classification_EfficientNetLite4}/app.py RENAMED
@@ -71,7 +71,8 @@ def inference(img):
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  title = "EfficientNet-Lite4"
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  description = "EfficientNet-Lite 4 is the largest variant and most accurate of the set of EfficientNet-Lite model. It is an integer-only quantized model that produces the highest accuracy of all of the EfficientNet models. It achieves 80.4% ImageNet top-1 accuracy, while still running in real-time (e.g. 30ms/image) on a Pixel 4 CPU."
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- examples = [[hf_hub_download('nateraw/gradio-guides-files', 'catonnx.jpg', repo_type='dataset', force_filename='catonnx.jpg')]]
 
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  interface = gr.Interface(
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  inference, gr.inputs.Image(type="filepath"), "label", title=title, description=description, examples=examples
 
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  title = "EfficientNet-Lite4"
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  description = "EfficientNet-Lite 4 is the largest variant and most accurate of the set of EfficientNet-Lite model. It is an integer-only quantized model that produces the highest accuracy of all of the EfficientNet models. It achieves 80.4% ImageNet top-1 accuracy, while still running in real-time (e.g. 30ms/image) on a Pixel 4 CPU."
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+ examples = [[hf_hub_download('nateraw/gradio-guides-files', 'catonnx.jpg', repo_type='dataset', force_filename='catonnx.jpg')],
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+ [('https://i.imgur.com/kVem6KB.jpeg'), 'cat_staring.jpg']]
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  interface = gr.Interface(
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  inference, gr.inputs.Image(type="filepath"), "label", title=title, description=description, examples=examples