tk

@nautilus28 is correct. Deleting the function on AWS Console and redeploying worked.

@yu4u Hi Yusuke-san, so for > In that case, it would be easy to write your code from scratch. > The problem you are going to solve is a simple...

@galoiscch I'm running into memory issues when running this in a conda env with Pytorch GPU and Tensorflow GPU (detection done by Tencent DSFD and not dlib): https://github.com/TencentYoutuResearch/FaceDetection-DSFD So I...

I had the same problem with the `imdb_db.mat` being only 200B in size but the `create_db.py` ended with a memory error.

Hi Yu4u-san, I tried but ended up with a `Memory Error`. I tried the `compress=True` option with the old code (still Memory Errors) so will do so with the updated...

No, when I ran demo.py, it was predicting correctly. I did not have to reverse the `>` sign. But I'll try again.

@hazxone I'm tring to train on 128 image size for gender only with smaller model of depth 10 and width 4. I guess this is a bad idea? Btw can...

But I got another memory error. ``` Traceback (most recent call last): File "create_db.py", line 106, in main() File "create_db.py", line 65, in main output1 = {"image": np.array(out_imgs), "gender": np.array(out_genders),...

I reduced size to 64 but still got a memory error although `imdb_db.mat` was created in `data` folder. ``` python create_db.py --output data/imdb_db.mat --db imdb --img_size 64 100%|█████████████████████████████████| 460723/460723 [02:56

@roryw10 https://github.com/matterport/Mask_RCNN/blob/master/samples/shapes/train_shapes.ipynb Under heading Training it says: > Train in two stages: > > Only the heads. Here we're freezing all the backbone layers and training only the randomly initialized...