yeephycho / densenet-tensorflow Goto Github PK

Hello, I have achieved very good performance in my dataset using your code. Right now, I want to use ImageNet pretrain model to improve performance more. Could you tell me how can I use it based on your code? I have convert imagenet pretrain model based on caffe model at https://github.com/shicai/DenseNet-Caffe

You can download my convert pretrain model at https://drive.google.com/open?id=1nby_ZC7ELkqaVaipPc8eKrzoHb05BGx4

The downloaded dataset is not right

hello,is your pretrained model the imagenet pretrained model?If not, what's your pretrained dataset?I want to use denset to do place recognition , can I use your pretrained model?Thank you thank you ~~

I used python build_image_data.py for own data
"../build_image_data.py"
It creates shard files :
train-00000-of-00002
train-00001-of-00002

Now when I run ./train.py it cant find file train.tfrecord
ValueError: Failed to find file: ./own_data_dir/train.tfrecord
This seems to be hardcoded in data_provider.py (line 77) as:
filenames = [os.path.join(DATA_DIR, "train.tfrecord")]

How can I get the code to produce a file named "train.tfrecord" insteald of several separare files, 1 for each shard?

Or is there some other way to combine shard-files to single file named .tfrecord?

First of all, I would like to thank your code. It is very useful for me. I have used it and obtain 81% in the flower dataset.
Now, I will use it for my dataset which includes 10.000 png images in the range 0-255. I have two questions for making/training my dataset

1. I saw in the build_image_data.py has png_to_jpeg(image_data), so if my dataset has png file, can it still work for converting tfrecord?
2. Because my image range is from 0-255. I guess we must normalize it to 0-1 for input of densenet network. For that purpose, I think we will change after the line 56 in the data provider.py as

image_raw = tf.image.decode_jpeg(image_encoded, channels=3)
image_raw = tf.cast(image_raw , tf.float32) * (1. / 255)

Am I right?