Merge pull request #74 from deklesen/main

Add zero-fills to progress output filenames, add sentence to README on how to convert to video

README.md

@@ -180,7 +180,7 @@ $ lightweight_gan \
   --num-image-tiles {count of image result}
 ```
 
-After run this command you will get folder near results image folder with postfix "-progress".
+After running this command you will get a new folder in the results folder, with postfix "-progress". You can convert the images to a video with ffmpeg using the command "ffmpeg -framerate 10 -pattern_type glob -i '*-ema.jpg' out.mp4".
 
 ![Show progress gif demonstration](./docs/show_progress/show-progress.gif)
 

lightweight_gan/lightweight_gan.py

@@ -1209,6 +1209,8 @@ def show_progress(self, num_images=4, types=['default', 'ema']):
         ext = self.image_extension
         latents = None
 
+        zfill_length = math.ceil(math.log10(len(checkpoints)))
+
         if not dir_full.exists():
             os.mkdir(dir_full)
 
@@ -1222,13 +1224,13 @@ def show_progress(self, num_images=4, types=['default', 'ema']):
             # regular
             if 'default' in types:
                 generated_image = self.generate_(self.GAN.G, latents)
-                path = str(self.results_dir / dir_name / f'{str(checkpoint)}.{ext}')
+                path = str(self.results_dir / dir_name / f'{str(checkpoint).zfill(zfill_length)}.{ext}')
                 torchvision.utils.save_image(generated_image, path, nrow=num_images)
 
             # moving averages
             if 'ema' in types:
                 generated_image = self.generate_(self.GAN.GE, latents)
-                path = str(self.results_dir / dir_name / f'{str(checkpoint)}-ema.{ext}')
+                path = str(self.results_dir / dir_name / f'{str(checkpoint).zfill(zfill_length)}-ema.{ext}')
                 torchvision.utils.save_image(generated_image, path, nrow=num_images)
 
     @torch.no_grad()