dev(narugo): upload inception v3

app.py

@@ -8,12 +8,20 @@ from huggingface_hub import hf_hub_download
 from imgutils.data import load_image
 from imgutils.utils import open_onnx_model
 
+_MODELS = [
+    ('nsfwjs.onnx', 224),
+    ('inception_v3.onnx', 299),
+]
+_MODEL_NAMES = [name for name, _ in _MODELS]
+_DEFAULT_MODEL_NAME = _MODEL_NAMES[0]
+_MODEL_TO_SIZE = dict(_MODELS)
+
 
 @lru_cache()
-def _onnx_model():
+def _onnx_model(name):
     return open_onnx_model(hf_hub_download(
         'deepghs/imgutils-models',
-        'nsfw/nsfwjs.onnx'
+        f'nsfw/{name}'
     ))
 
 
@@ -25,9 +33,9 @@ def _image_preprocess(image, size: int = 224) -> np.ndarray:
 _LABELS = ['drawings', 'hentai', 'neutral', 'porn', 'sexy']
 
 
-def predict(image):
-    input_ = _image_preprocess(image).astype(np.float32)
-    output_, = _onnx_model().run(['dense_3'], {'input_1': input_})
+def predict(image, model_name):
+    input_ = _image_preprocess(image, _MODEL_TO_SIZE[model_name]).astype(np.float32)
+    output_, = _onnx_model(model_name).run(['dense_3'], {'input_1': input_})
     return dict(zip(_LABELS, map(float, output_[0])))
 
 
@@ -36,6 +44,7 @@ if __name__ == '__main__':
         with gr.Row():
             with gr.Column():
                 gr_input_image = gr.Image(type='pil', label='Original Image')
+                gr_model = gr.Dropdown(_MODEL_NAMES, value=_DEFAULT_MODEL_NAME, label='Model')
                 gr_btn_submit = gr.Button(value='Tagging', variant='primary')
 
             with gr.Column():
@@ -43,7 +52,7 @@ if __name__ == '__main__':
 
         gr_btn_submit.click(
             predict,
-            inputs=[gr_input_image],
+            inputs=[gr_input_image, gr_model],
             outputs=[gr_ratings],
         )
     demo.queue(os.cpu_count()).launch()