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import io
import os
import requests
from PIL import Image
from model import get_caption_model, generate_caption
import gradio as gr
def get_model():
return get_caption_model()
caption_model = get_model()
def predict():
captions = []
pred_caption = generate_caption('tmp.jpg', caption_model)
captions.append(pred_caption)
for _ in range(4):
pred_caption = generate_caption('tmp.jpg', caption_model, add_noise=True)
if pred_caption not in captions:
captions.append(pred_caption)
#finalc = ' '.join([str(elem) for elem in captions])
return captions;
def launch(inputs):
img = Image.open(requests.get(inputs, stream=True).raw)
img = img.convert('RGB')
img.save('tmp.jpg')
o=predict()
str1=""
for ele in o:
str1 += "\n"+ele
os.remove('tmp.jpg')
return str1
iface = gr.Interface(launch, inputs="text", outputs="text",)
iface.launch(debug=True,)
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