import gradio as gr from fastai.vision.all import * import skimage learn = load_learner('export.pkl') labels = [ "แกงเขียวหวานไก่","แกงเทโพ","แกงเลียง","แกงจืดเต้าหู้หมูสับ","แกงจืดมะระยัดไส้", "แกงมัสมั่นไก่","แกงส้มกุ้ง","ไก่ผัดเม็ดมะม่วงหิมพานต์","ไข่เจียว","ไข่ดาว", "ไข่พะโล้","ไข่ลูกเขย","กล้วยบวชชี","ก๋วยเตี๋ยวคั่วไก่","กะหล่ำปลีผัดน้ำปลา", "กุ้งแม่น้ำเผา","กุ้งอบวุ้นเส้น","ขนมครก","ข้าวเหนียวมะม่วง","ข้าวขาหมู", "ข้าวคลุกกะปิ","ข้าวซอยไก่","ข้าวผัด","ข้าวผัดกุ้ง","ข้าวมันไก่", "ข้าวหมกไก่","ต้มข่าไก่","ต้มยำกุ้ง","ทอดมัน","ปอเปี๊ยะทอด", "ผักบุ้งไฟแดง","ผัดไท","ผัดกะเพรา","ผัดซีอิ๊วเส้นใหญ่","ผัดฟักทองใส่ไข่", "ผัดมะเขือยาวหมูสับ","ผัดหอยลาย","ฝอยทอง","พะแนงไก่","ยำถั่วพู", "ยำวุ้นเส้น","ลาบหมู","สังขยาฟักทอง","สาคูไส้หมู","ส้มตำ","หมูปิ้ง","หมูสะเต๊ะ","ห่อหมก" ] def predict(img): img = PILImage.create(img) pred,pred_idx,probs = learn.predict(img) return {labels[i]: float(probs[i]) for i in range(len(labels))} title = "Foodydudy Thai Food Classifier" description = "A 48-class Thai food classifier using model created by @gemmythegeek (AIB 2021). Created as a demo for Gradio and HuggingFace Spaces." article="

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" examples = ['padthai.jpg','panaeng.jpg','massaman.jpg'] interpretation='default' enable_queue=True gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()