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suresh-subramanian
commited on
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1db5c15
1
Parent(s):
3e73041
Update app.py
Browse files
app.py
CHANGED
@@ -3,18 +3,18 @@ import gradio as gr
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import datasets
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import torch
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from transformers import AutoFeatureExtractor, AutoModelForImageClassification
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from transformers import ViTFeatureExtractor, ViTForImageClassification
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dataset = datasets.load_dataset('beans')
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extractor = AutoFeatureExtractor.from_pretrained("suresh-subramanian/beans-classification")
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model = AutoModelForImageClassification.from_pretrained("suresh-subramanian/beans-classification")
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feature_extractor = ViTFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
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labels = dataset['train'].features['labels'].names
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def classify(im):
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features =
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with torch.no_grad():
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logits = model(features["pixel_values"])[-1]
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probability = torch.nn.functional.softmax(logits, dim=-1)
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import datasets
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import torch
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from transformers import AutoFeatureExtractor, AutoModelForImageClassification
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# from transformers import ViTFeatureExtractor, ViTForImageClassification
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dataset = datasets.load_dataset('beans')
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extractor = AutoFeatureExtractor.from_pretrained("suresh-subramanian/beans-classification")
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model = AutoModelForImageClassification.from_pretrained("suresh-subramanian/beans-classification")
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# feature_extractor = ViTFeatureExtractor.from_pretrained("google/vit-base-patch16-224")
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labels = dataset['train'].features['labels'].names
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def classify(im):
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features = extractor(im, return_tensors='pt')
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with torch.no_grad():
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logits = model(features["pixel_values"])[-1]
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probability = torch.nn.functional.softmax(logits, dim=-1)
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