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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))
image = gr.inputs.Image()
label = gr.outputs.Label(num_top_classes=48)
title= 'A Game For That - Gamification Using Snapshot Images'
examples = ['image.jpg','1.1.jpg','1.2.jpg','2.jpg','3.jpg','4.jpg', '5.jpg' ]
iface = gr.Interface(
fn=recognize_game_all,
inputs=image,
outputs=label,
title=title,
examples=examples)
#iface.launch(inline=False)
iface.launch(debug=True)
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