changed the dataset order

WisconsinAIVision · Aug 18, 2023 · 3bf7228 · 3bf7228
1 parent ce1d948
commit 3bf7228
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Showing 3 changed files with 88 additions and 92 deletions.
diff --git a/dataset_paths.py b/dataset_paths.py
@@ -5,161 +5,153 @@
     # = = = = = = = = = = = = = = LDM = = = = = = = = = = = = = = = = #
 
 
-
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/ldm_200step/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/progan',     
+        fake_path='../FAKE_IMAGES/CNN/test/progan',
+        data_mode='wang2020',
+        key='progan'
     ),
 
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/ldm_200step_cfg3/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/cyclegan',   
+        fake_path='../FAKE_IMAGES/CNN/test/cyclegan',
+        data_mode='wang2020',
+        key='cyclegan'
     ),
 
-
-
-
-    # = = = = = = = = = = = = = = GLIDE = = = = = = = = = = = = = = = = #
-
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/glide_100ddpm_27ddim/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/biggan/',   # Imagenet 
+        fake_path='../FAKE_IMAGES/CNN/test/biggan/',
+        data_mode='wang2020',
+        key='biggan'
     ),
 
-    dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/glide_75ddpm_27ddim/val.pickle',
-        data_mode='ours',
-    ),
 
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/glide_50ddpm_27ddim/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/stylegan',    
+        fake_path='../FAKE_IMAGES/CNN/test/stylegan',
+        data_mode='wang2020',
+        key='stylegan'
     ),
 
-    dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/glide_50ddim_27ddim/val.pickle',
-        data_mode='ours',
-    ),
 
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/glide_100ddpm_10ddim/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/gaugan',    # It is COCO 
+        fake_path='../FAKE_IMAGES/CNN/test/gaugan',
+        data_mode='wang2020',
+        key='gaugan'
     ),
 
 
-    # = = = = = = = = = = = = = = GUIDED = = = = = = = = = = = = = = = = #
-
     dict(
-        real_path='../imagenet/val.pickle',
-        fake_path='../FAKE_IMAGES/guided_imagenet_ddim25_cg1/val.pickle',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/stargan',  
+        fake_path='../FAKE_IMAGES/CNN/test/stargan',
+        data_mode='wang2020',
+        key='stargan'
     ),
 
 
-
-    # = = = = = = = = = = = = = = DALLE-MINI = = = = = = = = = = = = = = = = #
-
     dict(
-        real_path='../laion400m_data/val.pickle',
-        fake_path='../FAKE_IMAGES/DALLE-MINI',
-        data_mode='ours',
+        real_path='../FAKE_IMAGES/CNN/test/deepfake',   
+        fake_path='../FAKE_IMAGES/CNN/test/deepfake',
+        data_mode='wang2020',
+        key='deepfake'
     ),
 
 
-    # = = = = = = = = = = = = = = CNN = = = = = = = = = = = = = = = = #
-
-
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/biggan/',   # Imagenet 
-        fake_path='../FAKE_IMAGES/CNN/test/biggan/',
+        real_path='../FAKE_IMAGES/CNN/test/seeingdark',   
+        fake_path='../FAKE_IMAGES/CNN/test/seeingdark',
         data_mode='wang2020',
+        key='sitd'
     ),
 
-    dict(
-        real_path='../FAKE_IMAGES/CNN/test/cyclegan',   
-        fake_path='../FAKE_IMAGES/CNN/test/cyclegan',
-        data_mode='wang2020',
-    ),
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/gaugan',    # It is COCO 
-        fake_path='../FAKE_IMAGES/CNN/test/gaugan',
+        real_path='../FAKE_IMAGES/CNN/test/san',   
+        fake_path='../FAKE_IMAGES/CNN/test/san',
         data_mode='wang2020',
+        key='san'
     ),
 
+
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/progan',     
-        fake_path='../FAKE_IMAGES/CNN/test/progan',
+        real_path='../FAKE_IMAGES/CNN/test/crn',   # Images from some video games
+        fake_path='../FAKE_IMAGES/CNN/test/crn',
         data_mode='wang2020',
+        key='crn'
     ),
 
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/stylegan',    
-        fake_path='../FAKE_IMAGES/CNN/test/stylegan',
+        real_path='../FAKE_IMAGES/CNN/test/imle',   # Images from some video games
+        fake_path='../FAKE_IMAGES/CNN/test/imle',
         data_mode='wang2020',
+        key='imle'
     ),
-
+    
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/whichfaceisreal',    # It is FFHQ 
-        fake_path='../FAKE_IMAGES/CNN/test/whichfaceisreal',
-        data_mode='wang2020',
+        real_path='../imagenet/val.pickle',
+        fake_path='../FAKE_IMAGES/guided_imagenet_ddim25_cg1/val.pickle',
+        data_mode='ours',
+        key='guided'
     ),
 
+
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/crn',   # Images from some video games
-        fake_path='../FAKE_IMAGES/CNN/test/crn',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/ldm_200step/val.pickle',
+        data_mode='ours',
+        key='ldm_200'
     ),
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/imle',   # Images from some video games
-        fake_path='../FAKE_IMAGES/CNN/test/imle',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/ldm_200step_cfg3/val.pickle',
+        data_mode='ours',
+        key='ldm_200_cfg'
     ),
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/stargan',  
-        fake_path='../FAKE_IMAGES/CNN/test/stargan',
-        data_mode='wang2020',
-    ),
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/ldm_100step/val.pickle',
+        data_mode='ours',
+        key='ldm_100'
+     ),
+
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/stylegan2',   
-        fake_path='../FAKE_IMAGES/CNN/test/stylegan2',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/glide_100ddpm_27ddim/val.pickle',
+        data_mode='ours',
+        key='glide_100_27'
     ),
 
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/deepfake',   
-        fake_path='../FAKE_IMAGES/CNN/test/deepfake',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/glide_50ddpm_27ddim/val.pickle',
+        data_mode='ours',
+        key='glide_50_27'
     ),
 
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/san',   
-        fake_path='../FAKE_IMAGES/CNN/test/san',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/glide_100ddpm_10ddim/val.pickle',
+        data_mode='ours',
+        key='glide_100_10'
     ),
 
 
     dict(
-        real_path='../FAKE_IMAGES/CNN/test/seeingdark',   
-        fake_path='../FAKE_IMAGES/CNN/test/seeingdark',
-        data_mode='wang2020',
+        real_path='../laion400m_data/val.pickle',
+        fake_path='../FAKE_IMAGES/DALLE-MINI',
+        data_mode='ours',
+        key='dalle'
     ),
 
 
 
-
 ]
diff --git a/test.sh b/test.sh
@@ -0,0 +1 @@
+CUDA_VISIBLE_DEVICES=0 python3 validate.py --arch=CLIP:ViT-L/14  --ckpt=pretrained_weights/fc_weights.pth --result_folder=clip_vitl14 
diff --git a/validate.py b/validate.py
@@ -8,7 +8,7 @@
 import numpy as np
 from sklearn.metrics import average_precision_score, precision_recall_curve, accuracy_score
 from torch.utils.data import Dataset
-
+import sys
 from models import get_model
 from PIL import Image 
 import pickle
@@ -98,11 +98,13 @@ def validate(model, loader, find_thres=False):
 
     with torch.no_grad():
         y_true, y_pred = [], []
+        print ("Length of dataset: %d" %(len(loader)))
         for img, label in loader:
             in_tens = img.cuda()
 
             y_pred.extend(model(in_tens).sigmoid().flatten().tolist())
             y_true.extend(label.flatten().tolist())
+
     y_true, y_pred = np.array(y_true), np.array(y_pred)
 
     # ================== save this if you want to plot the curves =========== # 
@@ -194,7 +196,6 @@ def __init__(self,  real_path,
 
         stat_from = "imagenet" if arch.lower().startswith("imagenet") else "clip"
         self.transform = transforms.Compose([
-            transforms.Resize(256),
             transforms.CenterCrop(224),
             transforms.ToTensor(),
             transforms.Normalize( mean=MEAN[stat_from], std=STD[stat_from] ),
@@ -230,7 +231,9 @@ def __len__(self):
         return len(self.total_list)
 
     def __getitem__(self, idx):
+
         img_path = self.total_list[idx]
+
         label = self.labels_dict[img_path]
         img = Image.open(img_path).convert("RGB")
 
@@ -253,13 +256,13 @@ def __getitem__(self, idx):
     parser.add_argument('--real_path', type=str, default=None, help='dir name or a pickle')
     parser.add_argument('--fake_path', type=str, default=None, help='dir name or a pickle')
     parser.add_argument('--data_mode', type=str, default=None, help='wang2020 or ours')
-    parser.add_argument('--max_sample', type=int, default=10000, help='only check this number of images for both fake/real')
+    parser.add_argument('--max_sample', type=int, default=1000, help='only check this number of images for both fake/real')
 
     parser.add_argument('--arch', type=str, default='res50')
     parser.add_argument('--ckpt', type=str, default='./pretrained_weights/fc_weights.pth')
 
     parser.add_argument('--result_folder', type=str, default='result', help='')
-    parser.add_argument('--batch_size', type=int, default=64)
+    parser.add_argument('--batch_size', type=int, default=128)
 
     parser.add_argument('--jpeg_quality', type=int, default=None, help="100, 90, 80, ... 30. Used to test robustness of our model. Not apply if None")
     parser.add_argument('--gaussian_sigma', type=int, default=None, help="0,1,2,3,4.     Used to test robustness of our model. Not apply if None")
@@ -286,7 +289,7 @@ def __getitem__(self, idx):
 
 
 
-    for dataset_path in tqdm(dataset_paths):
+    for dataset_path in (dataset_paths):
         set_seed()
 
         dataset = RealFakeDataset(  dataset_path['real_path'], 
@@ -302,8 +305,8 @@ def __getitem__(self, idx):
         ap, r_acc0, f_acc0, acc0, r_acc1, f_acc1, acc1, best_thres = validate(model, loader, find_thres=True)
 
         with open( os.path.join(opt.result_folder,'ap.txt'), 'a') as f:
-            f.write( str(round(ap*100, 2))+'\n' )
+            f.write(dataset_path['key']+': ' + str(round(ap*100, 2))+'\n' )
 
         with open( os.path.join(opt.result_folder,'acc0.txt'), 'a') as f:
-            f.write( str(round(r_acc0*100, 2))+'  '+str(round(f_acc0*100, 2))+'  '+str(round(acc0*100, 2))+'\n' )
+            f.write(dataset_path['key']+': ' + str(round(r_acc0*100, 2))+'  '+str(round(f_acc0*100, 2))+'  '+str(round(acc0*100, 2))+'\n' )
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		CUDA_VISIBLE_DEVICES=0 python3 validate.py --arch=CLIP:ViT-L/14 --ckpt=pretrained_weights/fc_weights.pth --result_folder=clip_vitl14