Metantropia commited on
Commit
5324952
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1 Parent(s): 44353ac

Update app.py

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Files changed (1) hide show
  1. app.py +10 -10
app.py CHANGED
@@ -19,15 +19,15 @@ def classify_img(im):
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  labels = {v["label"]: v["score"] for v in ans}
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  return labels
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- def make_block(dem):
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- with dem:
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- gr.Markdown("""
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- # Este 'space' permite la inferencia los siguientes modelos open-source:
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  - Voice2Text: [Wav2Vec2](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-spanish)
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  - Sentiment Analysis: [Robertuito](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis)
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  - Image Classifier: [Swin-small-patch4](https://huggingface.co/microsoft/swin-small-patch4-window7-224)
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- Autor del demo: [ΜΕΤΑΝΘΡΩΠΙΑ](https://www.instagram.com/metantropia.jpg)
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- """)
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  with gr.Tabs():
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@@ -45,12 +45,12 @@ Autor del demo: [ΜΕΤΑΝΘΡΩΠΙΑ](https://www.instagram.com/metantropia.j
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  with gr.TabItem("Clasificación de Imágenes"):
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  with gr.Row():
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- image = gr.Image(label="Carga una imagen aquí")
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  label_image = gr.Label(num_top_classes=5)
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  b3 = gr.Button("Clasifica")
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- b1.click(audio2text,inputs=audio,outputs=transcripcion)
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- b2.click(text2sentiment,inputs=text,outputs=label)
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- b3.click(classify_img, inputs=image, outputs=label_image)
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  demo.launch()
 
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  labels = {v["label"]: v["score"] for v in ans}
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  return labels
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+ demo=gr.Blocks()
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+ with demo:
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+ gr.Markdown("""
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+ # Este 'Space' permite la inferencia los siguientes modelos open-source:
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  - Voice2Text: [Wav2Vec2](https://huggingface.co/facebook/wav2vec2-large-xlsr-53-spanish)
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  - Sentiment Analysis: [Robertuito](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis)
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  - Image Classifier: [Swin-small-patch4](https://huggingface.co/microsoft/swin-small-patch4-window7-224)
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+ - Autor del demo: [ΜΕΤΑΝΘΡΩΠΙΑ](https://www.instagram.com/metantropia.jpg)
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+ """)
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  with gr.Tabs():
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  with gr.TabItem("Clasificación de Imágenes"):
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  with gr.Row():
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+ image = gr.Image(label="Carga una Imagen")
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  label_image = gr.Label(num_top_classes=5)
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  b3 = gr.Button("Clasifica")
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+ b1.click(audio2text,inputs=audio,outputs=transcripcion)
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+ b2.click(text2sentiment,inputs=text,outputs=label)
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+ b3.click(classify_img, inputs=image, outputs=label_image)
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  demo.launch()