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@@ -39,6 +39,20 @@ Upload a grayscale JPG into the model inference section and it will cast a predi
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  Some are included in this repo. If the image contains an X, it is a negative cancer image.
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  If an image name contains a Y it is positive.
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  ## Results
 
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  Some are included in this repo. If the image contains an X, it is a negative cancer image.
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  If an image name contains a Y it is positive.
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+ ``` Python
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+
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+ from huggingface_hub import hf_hub_download
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+ from PIL import Image
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+
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+ abc= hf_hub_download(repo_id="oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans",
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+ filename="_X000a109d-56da-4c3f-8680-55afa04d6ae0.dcm.jpg.jpg")
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+ image = Image.open(abc)
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+ processor = AutoImageProcessor.from_pretrained("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans")
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+ model = AutoModelForImageClassification.from_pretrained("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans")
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+ inputs = processor(images=image, return_tensors="pt")
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+ outputs = model(**inputs)
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+
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+ ```
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  ## Results