fix: crash in inference script, errors in documentation

data/image_folder.py

@@ -94,18 +94,9 @@ def make_labeled_path_dataset(dir, paths, max_dataset_size=float("inf")):
         ):  # we allow B not having a label
             images.append(line_split[0])
 
-        elif len(line_split) == 2:
+        elif len(line_split) >= 2:
             images.append(line_split[0])
-            labels.append(line_split[1])
-
-        elif len(line_split) > 2:
-            images.append(line_split[0])
-
-            label_line = line_split[1]
-            for i in range(2, len(line_split)):
-                label_line += " " + line_split[i]
-
-            labels.append(label_line)
+            labels.append(" ".join(line_split[1:]))
 
     return (
         images[: min(max_dataset_size, len(images))],

docs/source/inference.rst

@@ -276,7 +276,7 @@ Download a pretrained model:
 Run the inference script
 ========================
 
-The ``--cond-in`` parameter specifies the conditioning image to use.
+The ``--cond_in`` parameter specifies the conditioning image to use.
 
 .. code:: bash
 

options/base_options.py

@@ -266,10 +266,11 @@ def _after_parse(self, opt, set_device=True):
 
         return self.opt
 
-    def parse(self):
+    def parse(self, save_config=True):
         """Parse our options, create checkpoints directory suffix, and set up gpu device."""
         self.opt = self.gather_options()
-        self.save_options()
+        if save_config:
+            self.save_options()
         opt = self._after_parse(self.opt)
         return opt
 

options/inference_diffusion_options.py

@@ -98,7 +98,7 @@ def initialize(self, parser):
         )
 
         parser.add_argument(
-            "--cls_value",
+            "--cls",
             type=int,
             default=-1,
             help="override input bbox classe for generation",

scripts/gen_single_image.py

@@ -142,5 +142,5 @@ def inference(args):
 
 
 if __name__ == "__main__":
-    opt = InferenceGANOptions().parse()
+    opt = InferenceGANOptions().parse(save_config=False)
     inference(opt)

scripts/gen_single_image_diffusion.py

@@ -186,7 +186,7 @@ def generate(
     cond_persp_vertical,
     alg_diffusion_cond_image_creation,
     alg_diffusion_sketch_canny_thresholds,
-    cls_value,
+    cls,
     alg_diffusion_super_resolution_downsample,
     alg_diffusion_guidance_scale,
     data_refined_mask,
@@ -268,9 +268,7 @@ def generate(
                 elts = line.rstrip().split()
                 bboxes.append([int(elts[1]), int(elts[2]), int(elts[3]), int(elts[4])])
                 if conditioning:
-                    if cls_value > 0:
-                        cls = cls_value
-                    else:
+                    if cls <= 0:
                         cls = int(elts[0])
                 else:
                     cls = 1
@@ -760,5 +758,5 @@ def inference(args):
 
 
 if __name__ == "__main__":
-    args = InferenceDiffusionOptions().parse()
+    args = InferenceDiffusionOptions().parse(save_config=False)
     inference(args)

tests/test_run_mask_online_ref.py

@@ -36,7 +36,7 @@
     ["cut", "unaligned_labeled_mask_online_ref"],
 ]
 conditionings = [
-    "alg_palette_conditioning",
+    "alg_diffusion_cond_embed",
     "alg_palette_cond_image_creation",
 ]
 

tests/test_run_mask_ref.py

@@ -36,7 +36,7 @@
     ["cut", "unaligned_labeled_mask_ref"],
 ]
 conditionings = [
-    "alg_palette_conditioning",
+    "alg_diffusion_cond_embed",
     "alg_palette_cond_image_creation",
 ]
 

util/visualizer.py

@@ -458,12 +458,12 @@ def plot_metrics_dict(
             json.dump(self.metrics_dict, fp)
 
     def plot_current_metrics(self, epoch, counter_ratio, metrics):
-        """display the current fid values on visdom display: dictionary of fid labels and values
+        """display the current metrics values on visdom display
 
         Parameters:
             epoch (int)           -- current epoch
             counter_ratio (float) -- progress (percentage) in the current epoch, between 0 to 1
-            fids (OrderedDict)  -- training fid values stored in the format of (name, float) pairs
+            metrics (OrderedDict)  -- training metrics values stored in the format of (name, float) pairs
         """
         self.plot_metrics_dict(
             "metric",
@@ -476,7 +476,7 @@ def plot_current_metrics(self, epoch, counter_ratio, metrics):
         )
 
     def plot_current_D_accuracies(self, epoch, counter_ratio, accuracies):
-        """display the current fid values on visdom display: dictionary of fid labels and values
+        """display the current accuracies values on visdom display
 
         Parameters:
             epoch (int)           -- current epoch
@@ -505,7 +505,7 @@ def plot_current_APA_prob(self, epoch, counter_ratio, p):
         )
 
     def plot_current_miou(self, epoch, counter_ratio, miou):
-        """display the current fid values on visdom display: dictionary of fid labels and values
+        """display the current miou values on visdom display
 
         Parameters:
             epoch (int)           -- current epoch