fixes failure when numpy version is 1.16.2.

classify_nsfw.py

@@ -47,7 +47,7 @@ def main(argv):
 
         if input_type == InputType.TENSOR:
             if args.image_loader == IMAGE_LOADER_TENSORFLOW:
-                fn_load_image = create_tensorflow_image_loader(tf.Session(graph=tf.Graph()))
+                fn_load_image = create_tensorflow_image_loader(tf.Session(graph=tf.get_default_graph()))
             else:
                 fn_load_image = create_yahoo_image_loader()
         elif input_type == InputType.BASE64_JPEG:

eval/batch_classify.py

@@ -64,7 +64,7 @@ def main(argv):
     input_type = InputType.TENSOR
     model = OpenNsfwModel()
 
-    filenames = glob.glob(args.source + "/*.jpg")
+    filenames = sorted(glob.glob(args.source + "/*.jpg"))
     num_files = len(filenames)
 
     num_batches = int(num_files / batch_size)

eval/eval.py

@@ -42,6 +42,7 @@ def test(first, second):
     result = {
         'min': np.amin(delta),
         'max': np.amax(delta),
+        'max-index': delta.argmax(),
         'median': np.median(delta),
         'mean': np.mean(delta),
         'std': np.std(delta),
@@ -80,7 +81,10 @@ def main(argv):
     other_classifications = classification_matrix(other)
 
     print('SFW:')
-    print(test(original_classifications[:, 0], other_classifications[:, 0]))
+    result = test(original_classifications[:, 0], other_classifications[:, 0]);
+    print(result)
+    index = result["max-index"]
+    print(original[index])
 
     print()
     print('NSFW:')

eval/eval_accurracy.py

@@ -0,0 +1,85 @@
+import sys
+import operator
+import argparse
+import numpy as np
+
+
+def load_classifications(filename):
+    is_first = True
+
+    results = {}
+
+    with open(filename, 'r') as f:
+        for line in f:
+            if is_first:
+                is_first = False
+                continue
+
+            parts = line.split('\t')
+
+            filename = parts[0]
+            sfw_score = float(parts[1])
+            nsfw_score = float(parts[2])
+
+            results[filename] = (sfw_score, nsfw_score)
+
+    return results
+
+
+def classification_matrix(classifications):
+    results = np.zeros(shape=(len(classifications), 2))
+
+    for i, classification in enumerate(classifications):
+        results[i] = np.array(classification[1])
+
+    return results
+
+
+def test_acc(nsfw):
+    count = len(nsfw)
+    result = {
+        'sfw': (nsfw < 0.5).sum() / count,
+        'nsfw': (nsfw >= 0.7).sum() / count,
+        'sexy': ((nsfw >= 0.5) & (nsfw < 0.7)).sum() / count,
+    }
+
+    return result
+
+
+def main(argv):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("input",
+                        help="File containing classifications")
+
+    parser.add_argument("-n", "--nsfw",
+                        help="write out wrong NSFW classifications to file")
+
+    parser.add_argument("-s", "--sfw",
+                        help="write out wrong SFW classifications to file")
+
+    args = parser.parse_args()
+    filename_input = args.input
+
+    result = load_classifications(filename_input)
+
+    result = sorted(result.items(), key=operator.itemgetter(0))
+
+    print("Found", len(result), "entries")
+
+    classifications = classification_matrix(result)
+
+    acc_res = test_acc(classifications[:, 1]);
+    print(acc_res)
+
+    if args.nsfw:
+        i = 0
+        with open(args.nsfw, 'w') as o:
+            for v in classifications[:, 1]:
+                if v < 0.7:
+                    o.write('{}\n'.format(result[i][0]))
+                i += 1
+
+
+if __name__ == "__main__":
+    main(sys.argv)

eval/pick_wrong_test_images.py

@@ -0,0 +1,36 @@
+import os
+import sys
+import argparse
+
+
+def main(argv):
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("input",
+                        help="File containing wrong images")
+
+    parser.add_argument("-s", "--source", required=True,
+                        help="Folder containing the test images")
+
+    parser.add_argument("-o", "--output", required=True,
+                        help="Folder to contain the wrong label images")
+
+    args = parser.parse_args()
+    filename_input = args.input
+
+    if os.path.exists(args.output) & (not os.path.isdir(args.output)):
+        print("{} exists but not a directory".format(args.output))
+        return
+    elif not os.path.exists(args.output):
+        os.mkdir(args.output)
+
+    with open(filename_input, 'r') as f:
+        for line in f:
+            line = line.rstrip()
+            source_file = os.path.join(args.source, line)
+            dest_file = os.path.join(args.output, line)
+            os.rename(source_file, dest_file)
+
+
+if __name__ == "__main__":
+    main(sys.argv)