Nidhal-ch commited on
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7e1d4d8
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1 Parent(s): 180c806

Update app.py

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Files changed (1) hide show
  1. app.py +11 -7
app.py CHANGED
@@ -79,12 +79,12 @@ hyperparameters = {
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  }
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  results_data = {
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- 'SSD300': {'Transfer Pruning':{'map': [0.6, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]},
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- 'VIB Pruning':{'map': [0.9, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]}},
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- 'SSD512': {'Transfer Pruning':{'map': [0.6, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]},
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- 'VIB Pruning':{'map': [0.9, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]}},
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- 'DETR': {'SPARK':{'map': [0.6, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]},
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- 'VOC':{'map': [0.9, 0.65, 0.7, 0.75], 'flops': [1e9, 1.1e9, 1.2e9, 1.3e9], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6]}},
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  }
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  # Title of the research
@@ -125,14 +125,18 @@ with col1:
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  'Model': [model]*4,
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  'mAP': results[pruning]['map'],
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  'FLOPs': results[pruning]['flops'],
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- 'Params': results[pruning]['params']
 
 
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  })
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  else:
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  df_results = pd.DataFrame({
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  'Model': [model]*4,
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  'mAP': results[dataset]['map'],
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  'FLOPs': results[dataset]['flops'],
 
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  'Params': results[dataset]['params']
 
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  })
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  }
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  results_data = {
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+ 'SSD300': {'Transfer Pruning':{'map': [77.79, 77.86 , 77.06, 75.08], 'flops': [11.1, 6.85, 5.08, 3.38],'flopsd':['0.0%','0.0%','0.0%',"0.0%"], 'params': [49.2, 32.5, 25.7, 19.4],'paramsd':['0.0%','0.0%','0.0%',"0.0%"]},
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+ 'VIB Pruning':{'map': [77.79, 0.65, 0.7], 'flops': [1e9, 1.1e9, 1.2e9],'flopsd':['0.0%','0.0%','0.0%'], 'params': [1e6, 1.1e6, 1.2e6, 1.3e6],'paramsd':['0.0%','0.0%','0.0%'],}},
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+ 'SSD512': {'Transfer Pruning':{'map': [80.9, 81.05 , 80.45, 78.82], 'flops': [46.2, 31.42, 25.6, 20.1],'flopsd':['0.0%','0.0%','0.0%',"0.0%"], 'params': [58.5, 41.8, 35.0, 28.7],'paramsd':['0.0%','0.0%','0.0%',"0.0%"],},
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+ 'VIB Pruning':{'map': [80.9, 0.65], 'flops': [1e9, 1.1e9],'flopsd':['0.0%','0.0%'], 'params': [1e6, 1.1e6],'flopsd':['0.0%','0.0%']}},
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+ 'DETR': {'SPARK':{'map': [0.6, 0.65, 0.7], 'flops': [1e9, 1.1e9, 1.2e9],'flopsd':['0.0%','0.0%','0.0%'], 'params': [1e6, 1.1e6, 1.2e6],'flopsd':['0.0%','0.0%','0.0%'],},
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+ 'VOC':{'map': [0.9, 0.65, 0.7], 'flops': [1e9, 1.1e9, 1.2e9],'flopsd':['0.0%','0.0%','0.0%'], 'params': [1e6, 1.1e6, 1.2e6],'flopsd':['0.0%','0.0%','0.0%'],}},
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  }
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  # Title of the research
 
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  'Model': [model]*4,
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  'mAP': results[pruning]['map'],
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  'FLOPs': results[pruning]['flops'],
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+ 'down by': results[pruning]['flopsd'],
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+ 'Params': results[pruning]['params'],
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+ 'down by': results[pruning]['paramsd'],
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  })
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  else:
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  df_results = pd.DataFrame({
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  'Model': [model]*4,
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  'mAP': results[dataset]['map'],
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  'FLOPs': results[dataset]['flops'],
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+ 'down by': results[dataset]['flopsd'],
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  'Params': results[dataset]['params']
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+ 'down by': results[dataset]['paramsd'],
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  })
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