LPX55 commited on
Commit
d5a469d
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1 Parent(s): d62865a

Update app.py

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Files changed (1) hide show
  1. app.py +17 -13
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")
@@ -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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-
 
 
 
 
 
 
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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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-
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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)}")
@@ -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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- # try:
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- # pred = model.predict(np.expand_dims(img_pil / 255, 0))
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- # result_5 = {
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- # 'AI': pred[0],
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- # 'Real': pred[1]
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- # }
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- # except Exception as e:
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- # label_3 = f"Error: {str(e)}"
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  # Combine results
@@ -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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- # "ALSv": label_5
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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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+
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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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+
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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