LPX55 commited on
Commit
1d42aa4
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1 Parent(s): 7b2b2e4

Update app.py

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Files changed (1) hide show
  1. app.py +18 -12
app.py CHANGED
@@ -8,6 +8,8 @@ import pandas as pd
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  import warnings
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  import math
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  import numpy as np
 
 
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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")
@@ -47,6 +49,10 @@ def softmax(vector):
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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)}")
@@ -72,9 +78,9 @@ def predict_image(img, confidence_threshold):
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  # Check if either class meets the confidence threshold
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  if result_1['artificial'] >= confidence_threshold:
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- label_1 = f"Label: artificial, Confidence: {result_1['artificial']:.4f}"
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  elif result_1['real'] >= confidence_threshold:
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- label_1 = f"Label: real, Confidence: {result_1['real']:.4f}"
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  else:
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  label_1 = "Uncertain Classification"
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  except Exception as e:
@@ -92,9 +98,9 @@ def predict_image(img, confidence_threshold):
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  # Check if either class meets the confidence threshold
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  if result_2['AI Image'] >= confidence_threshold:
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- label_2 = f"Label: AI Image, Confidence: {result_2['AI Image']:.4f}"
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  elif result_2['Real Image'] >= confidence_threshold:
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- label_2 = f"Label: Real Image, Confidence: {result_2['Real Image']:.4f}"
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  else:
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  label_2 = "Uncertain Classification"
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  except Exception as e:
@@ -120,9 +126,9 @@ def predict_image(img, confidence_threshold):
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  # Check if either class meets the confidence threshold
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  if result_3['AI'] >= confidence_threshold:
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- label_3 = f"Label: AI, Confidence: {result_3['AI']:.4f}"
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  elif result_3['Real'] >= confidence_threshold:
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- label_3 = f"Label: Real, Confidence: {result_3['Real']:.4f}"
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  else:
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  label_3 = "Uncertain Classification"
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  except Exception as e:
@@ -148,9 +154,9 @@ def predict_image(img, confidence_threshold):
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  # Check if either class meets the confidence threshold
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  if result_4['AI'] >= confidence_threshold:
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- label_4 = f"Label: AI, Confidence: {result_4['AI']:.4f}"
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  elif result_4['Real'] >= confidence_threshold:
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- label_4 = f"Label: Real, Confidence: {result_4['Real']:.4f}"
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  else:
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  label_4 = "Uncertain Classification"
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  except Exception as e:
@@ -168,10 +174,10 @@ def predict_image(img, confidence_threshold):
168
 
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  # Combine results
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  combined_results = {
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- "SwinV2": label_1,
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- "AI-vs-Real-Image-Detection": label_2,
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- "Organika/sdxl-detector": label_3,
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- "cmckinle/sdxl-flux-detector": label_4,
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  # "ALSv": label_5
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  }
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  import warnings
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  import math
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  import numpy as np
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+ from utils import call_inference
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+
13
 
14
  # Suppress warnings
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  warnings.filterwarnings("ignore", category=UserWarning, message="Using a slow image processor as `use_fast` is unset")
 
49
 
50
  @spaces.GPU(duration=10)
51
  def predict_image(img, confidence_threshold):
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+
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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)}")
 
78
 
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  # Check if either class meets the confidence threshold
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  if result_1['artificial'] >= confidence_threshold:
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+ label_1 = f"AI, Confidence: {result_1['artificial']:.4f}"
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  elif result_1['real'] >= confidence_threshold:
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+ label_1 = f"Real, Confidence: {result_1['real']:.4f}"
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  else:
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  label_1 = "Uncertain Classification"
86
  except Exception as e:
 
98
 
99
  # Check if either class meets the confidence threshold
100
  if result_2['AI Image'] >= confidence_threshold:
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+ label_2 = f"AI, Confidence: {result_2['AI Image']:.4f}"
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  elif result_2['Real Image'] >= confidence_threshold:
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+ label_2 = f"Real, Confidence: {result_2['Real Image']:.4f}"
104
  else:
105
  label_2 = "Uncertain Classification"
106
  except Exception as e:
 
126
 
127
  # Check if either class meets the confidence threshold
128
  if result_3['AI'] >= confidence_threshold:
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+ label_3 = f"AI, Confidence: {result_3['AI']:.4f}"
130
  elif result_3['Real'] >= confidence_threshold:
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+ label_3 = f"Real, Confidence: {result_3['Real']:.4f}"
132
  else:
133
  label_3 = "Uncertain Classification"
134
  except Exception as e:
 
154
 
155
  # Check if either class meets the confidence threshold
156
  if result_4['AI'] >= confidence_threshold:
157
+ label_4 = f"AI, Confidence: {result_4['AI']:.4f}"
158
  elif result_4['Real'] >= confidence_threshold:
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+ label_4 = f"Real, Confidence: {result_4['Real']:.4f}"
160
  else:
161
  label_4 = "Uncertain Classification"
162
  except Exception as e:
 
174
 
175
  # Combine results
176
  combined_results = {
177
+ "SwinV2/detect": label_1,
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+ "ViT/AI-vs-Real": label_2,
179
+ "Swin/SDXL": label_3,
180
+ "Swin/SDXL-FLUX": label_4,
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  # "ALSv": label_5
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  }
183