mhdiqbalpradipta commited on
Commit
ff2d287
1 Parent(s): 03f7a50

Update app.py

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Files changed (1) hide show
  1. app.py +12 -24
app.py CHANGED
@@ -1,34 +1,22 @@
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  import gradio as gr
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  from transformers import pipeline
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- from fastapi import FastAPI
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- # Memuat model untuk klasifikasi makanan padang
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  food_classifier = pipeline(task="image-classification", model="mhdiqbalpradipta/minang_food_classification")
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- def prediksi_makanan(gambar):
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- # Melakukan prediksi menggunakan model
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- hasil = food_classifier(images=gambar)[0]
 
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- # Menyimpan label dan skor
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- label_makanan = hasil['label']
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- skor = hasil['score']
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-
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- return f"Makanan: {label_makanan}, Skor: {skor:.2f}"
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-
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- # Antarmuka Gradio
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  image_in = gr.Image(type='pil')
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  label_out = "text"
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- contoh_gambar = ['ayam_goreng.jpg', 'ayam_pop.jpg', 'daging_rendang.jpg', 'dendeng_batokok.jpg', 'gulai_ikan.jpg', 'gulai_tambusu.jpg', 'gulai_tunjang.jpg', 'telur_balado.jpg', 'telur_dadar.jpg']
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-
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- intf = gr.Interface(fn=prediksi_makanan, inputs=image_in, outputs=label_out, examples=contoh_gambar, title="Pengklasifikasi Makanan Minang", description="Unggah gambar makanan untuk mengklasifikasikannya menjadi hidangan Minang.")
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-
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- # if __name__ == "__main__":
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- app = FastAPI()
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-
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- @app.get('/')
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- async def root():
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- return 'Gradio app is running at /gradio', 200
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- app = gr.mount_gradio_app(app, intf, path='/gradio')
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- # intf.launch(share=False)
 
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  import gradio as gr
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  from transformers import pipeline
 
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+ # Load the model for food classification
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  food_classifier = pipeline(task="image-classification", model="mhdiqbalpradipta/minang_food_classification")
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+ def predict_food(image):
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+ # Perform prediction using the model
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+ result = food_classifier(images=image)[0]
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+ # Save label and score
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+ food_label = result['label']
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+ score = result['score']
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+ return f"Food: {food_label}, Score: {score:.2f}"
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+ # Gradio Interface
 
 
 
 
 
 
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  image_in = gr.Image(type='pil')
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  label_out = "text"
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+ example_images = ['ayam_goreng.jpg', 'ayam_pop.jpg', 'daging_rendang.jpg', 'dendeng_batokok.jpg', 'gulai_ikan.jpg', 'gulai_tambusu.jpg', 'gulai_tunjang.jpg', 'telur_balado.jpg', 'telur_dadar.jpg']
 
 
 
 
 
 
 
 
 
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+ intf = gr.Interface(fn=predict_food, inputs=image_in, outputs=label_out, examples=example_images, title="Minang Food Classifier", description="Upload an image of food to classify it into Minang dishes.")
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+ intf.launch(share=False);