LayBraid commited on
Commit
744fb8a
1 Parent(s): 5b62fe7
Files changed (1) hide show
  1. app.py +39 -4
app.py CHANGED
@@ -1,10 +1,45 @@
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  import gradio as gr
 
 
 
 
 
 
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- def send_inputs(inputs):
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- print(inputs)
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- return "Hello"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  if __name__ == "__main__":
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- gr.Interface(fn=send_inputs, inputs=["text"], outputs="image").launch()
 
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  import gradio as gr
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+ import os
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+ import clip
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+ import torch
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+ from torchvision import transforms
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+ from PIL import Image
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+ from torchvision.datasets import CIFAR100
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+ model, preprocess = clip.load('ViT-B/32', "cpu")
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+
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+ cifar100 = CIFAR100(root=os.path.expanduser("~/.cache"), download=True, train=False)
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+
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+
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+ IMG_SIZE = 32 if torch.cuda.is_available() else 32
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+ COMPOSED_TRANSFORMERS = transforms.Compose([
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+ transforms.Resize(IMG_SIZE),
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+ transforms.ToTensor(),
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+ ])
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+
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+ NORMALIZE_TENSOR = transforms.Normalize(
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+ mean=[0.485, 0.456, 0.406],
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+ std=[0.229, 0.224, 0.225]
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+ )
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+
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+
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+ def np_array_to_tensor_image(img, width=IMG_SIZE, height=IMG_SIZE, device='cpu'):
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+ image = Image.fromarray(img).convert('RGB').resize((width, height))
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+ image = COMPOSED_TRANSFORMERS(image).unsqueeze(0)
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+ return image.to(device, torch.float)
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+
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+
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+ def normalize_tensor(tensor: torch.tensor) -> torch.tensor:
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+ return NORMALIZE_TENSOR(tensor)
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+
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+
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+ def send_inputs(img):
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+ img = np_array_to_tensor_image(img)
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+ img = normalize_tensor(img)
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+ result = model(img)
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+ return result
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  if __name__ == "__main__":
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+ gr.Interface(fn=send_inputs, inputs=["image"], outputs="text").launch()