Upload 4 files

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import timm
+import random
+import pickle
+
+
+infile = open('gamename_dict.pkl','rb')
+game_name_dict = pickle.load(infile)
+infile.close()
+
+learn=load_learner('convnext_nano_4freeze_5epochs_on_jpg_26error.pkl') 
+categories=learn.dls.vocab
+categories=[game_name_dict[gn] for gn in categories]
+
+def recognize_game(img):
+    img= PILImage.create(img)
+    pred,idx,probs=learn.predict(img)
+    return pred,str(100*float(dict(zip(categories, probs))[pred]))[:4]+"%"
+
+def recognize_game_all(img):
+    img= PILImage.create(img)
+    pred,idx,probs=learn.predict(img)
+    img.save(pred+str(random.randrange(1,10000))+'.jpg')
+    return dict(zip(categories, map(float,probs)))
+
+
+image = gr.inputs.Image(shape=(224,224))
+label = gr.outputs.Label(num_top_classes=48)
+title= 'Boardgame recognizer'
+examples = ['bloodrage.jpg','nemesis.jpg','root.jpg','scythe.jpg' ]
+
+iface = gr.Interface(fn=recognize_game_all, inputs=image, outputs=label,title=title, examples=examples)
+iface.launch(inline=False)

convnext_nano_4freeze_5epochs_on_jpg_26error.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1bd67c691c1df93eac4323d900187b5b41f855ebf7f2f7808d7c46059e277f88
+size 62802417

gamename_dict.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:173e69dde614d3e437fa470b6bc33d7e515af47a7514dd0e881bd2e1b415c44a
+size 4150

requirements.txt

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+fastai
+scikit-image
+timm