Question: How to serve the trained models? about pose-gan HOT 4 CLOSED

I never used serving. So I cant help you with that.
Also I would not advise you to use this models in production, the quality of generated images is rather low compared to production requirements. Moreover it will not generalize outside the dataset.
The closest thing I have is demo.py, usage is following:

1. Put an image of your person to data/source_image.jpg
2. Put image from which to extract pose to data/target_images
3. Download pose estimator and some checkpoint (see Readme where)
4. python demo.py --generator_checkpoint path_to_checkpoint --warp_skip mask --dataset dataset_name --cache_pose_rep 0
5. Result should be in output/generated_images

There are already some images in the repository, you will need to remove them/

from pose-gan.

Ah, sorry. This was written for market. You should change resize in the line:

from pose-gan.

Thanks for the detailed explanation.
I'm getting the following error when I followed the above steps.
Traceback (most recent call last):
File "demo.py", line 108, in <module>
input_images, target_images, generated_images, names = generate_images(dataset, generator, args.use_input_pose)
File "/home/shan/Documents/pg/test.py", line 90, in generate_images
batch, name = dataset.next_generator_sample_test(with_names=True)
File "/home/shan/Documents/pg/pose_dataset.py", line 174, in next_generator_sample_test
batch = self.load_batch(index, False, True)
File "/home/shan/Documents/pg/pose_dataset.py", line 153, in load_batch
result = [self.load_image_batch(pair_df, 'from')]
File "/home/shan/Documents/pg/pose_dataset.py", line 131, in load_image_batch
batch[i] = imread(os.path.join(self._images_dir_test, p[direction]))

ValueError: could not broadcast input array from shape (128,64,3) into shape (256,256,3)

from pose-gan.

OK, it's working now
Thanks 😄

from pose-gan.