how to get the trainset on places2?

[knazeri]

how to get the trainset on places2?

[knazeri]

@ljjcoder If you already have downloaded the high-resolution Places2 dataset, you can set INPUT_SIZE: 256 in your configuration file and change the following line in the code and pass centerCrop=False argument to the resize method to prevent center cropping:

edge-connect/src/dataset.py

Line 141 in 97c28c6

mask = self.resize(mask, imgh, imgw)

If you don't have the high-resolution dataset, you can download 256x256 version from Places2 website under Data of Places-Extra69 section. You can also find a 256x256 version for the validation and test sets on the same page.

[ljjcoder]

@knazeri ，thanks for your reply！do you mean that it only needs to change the mask = self.resize(mask, imgh, imgw) to mask = self.resize(mask, imgh, imgw,centerCrop=False)? if only
do this ,the mask resize to 256 directly but the img also use center crop. I guess it also need the
def resize(self, img, height, width, centerCrop=True): to def resize(self, img, height, width, centerCrop=False):. Is it right?

[ljjcoder]

@knazeri I also ask what is different between Data of Places-Extra69 and Data of Places365-Challenge 2016? which one do you use? or both of them are used?

[knazeri]

@ljjcoder You don't need to change the method definition. Only change the method call. Of course that is if you have already downloaded the high-resolution version of the Places2 dataset.
We have used the 256x256 version of Places2-Challenge 2016 full dataset for training!

[ljjcoder]

@knazeri yes, I download the high-resolution version of the Places2. I still feel confused that if I just change change the the mask = self.resize(mask, imgh, imgw) to mask = self.resize(mask, imgh, imgw,centerCrop=False), the original image still use center crop. it is same as your training data?

[knazeri]

@ljjcoder Honestly it doesn't really make any difference. You can either center crop an image or resize it to a fixed size. In either of these scenarios, the mask hides some part of the image and your network learns to inpaint the missing part! Like I mentioned before, our training dataset was the 256x256 version of the Places2 dataset.

[anshen666]

你好，我最近也在跑这个代码。可以加你交流一下吗？我的微信：loveanshen 我的QQ：519838354 我的邮箱：[email protected] 非常期待你百忙中的回复

[napohou]

Files in Data of Places-Extra69 section is just 1.4G(256*256), it contains only 98,721 images for training. Is it enough to train the model?