Update app.py
Browse files
app.py
CHANGED
@@ -9,6 +9,8 @@ import warnings
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import math
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import numpy as np
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from utils.goat import call_inference
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# Suppress warnings
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warnings.filterwarnings("ignore", category=UserWarning, message="Using a slow image processor as `use_fast` is unset")
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@@ -45,13 +47,16 @@ labels_4 = ['AI', 'Real']
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def softmax(vector):
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e = np.exp(vector - np.max(vector)) # for numerical stability
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return e / e.sum()
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@spaces.GPU(duration=10)
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def predict_image(img, confidence_threshold):
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response5_raw = call_inference(img)
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response5 = response5_raw.json()
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# Ensure the image is a PIL Image
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if not isinstance(img, Image.Image):
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raise ValueError(f"Expected a PIL Image, but got {type(img)}")
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@@ -161,14 +166,13 @@ def predict_image(img, confidence_threshold):
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except Exception as e:
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label_4 = f"Error: {str(e)}"
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# label_3 = f"Error: {str(e)}"
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# Combine results
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@@ -177,7 +181,7 @@ def predict_image(img, confidence_threshold):
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"ViT/AI-vs-Real": label_2,
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"Swin/SDXL": label_3,
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"Swin/SDXL-FLUX": label_4,
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}
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return combined_results
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import math
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import numpy as np
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from utils.goat import call_inference
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import io
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import sys
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# Suppress warnings
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warnings.filterwarnings("ignore", category=UserWarning, message="Using a slow image processor as `use_fast` is unset")
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def softmax(vector):
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e = np.exp(vector - np.max(vector)) # for numerical stability
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return e / e.sum()
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def convert_pil_to_bytes(image, format='JPEG'):
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img_byte_arr = io.BytesIO()
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image.save(img_byte_arr, format=format)
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img_byte_arr = img_byte_arr.getvalue()
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return img_byte_arr
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@spaces.GPU(duration=10)
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def predict_image(img, confidence_threshold):
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# Ensure the image is a PIL Image
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if not isinstance(img, Image.Image):
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raise ValueError(f"Expected a PIL Image, but got {type(img)}")
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except Exception as e:
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label_4 = f"Error: {str(e)}"
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try:
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img_bytes = convert_pil_to_bytes(img_pil)
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response5_raw = call_inference(img_bytes)
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response5 = response5_raw.json()
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print(response5)
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except Exception as e:
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label_5 = f"Error: {str(e)}"
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# Combine results
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"ViT/AI-vs-Real": label_2,
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"Swin/SDXL": label_3,
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"Swin/SDXL-FLUX": label_4,
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"GOAT": label_5
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}
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return combined_results
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