2h4dl

can't convert model from tensorflow to caffe with tf.layrers.batch_normalization

7

Platform (like ubuntu 16.04/win10): ` ubuntu 16.04 ` Python version: ` python 2.7 ` Source framework with version (like Tensorflow 1.4.1 with GPU): ` Tensorflow 1.12 ` Destination framework with...

how to resize gif image and write to file or buffer

28

I have a image like below:  I want to scale it and write to buffer or file, how to do it?

how to detect colorspace of an image

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I'm using `pyvips.Image.icc_transform` to convert an image's color space to sRGB. This API with a tiny, little flaw is also covert a sRGB image to sRGB. I need to detect...

write_to_buffer is slow as write_to_file

7

Hello, I'm using write_to_buffer to conver image to a binary object, but this is so slow. pyvips:2.1.11 libvips:8.9.1 os: windows 10 image size: 16MB image url: https://github.com/2h4dl/image-processing-with-opencv-dlib/blob/master/0a4f3400-4b63-4d25-9354-01d472cff0ef.png wrtie_to_buffer cost time:...

vips_colourspace: no known route from 'labs' to 'rgb'

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``` pyvips.error.Error: unable to call sharpen vips_colourspace: no known route from 'labs' to 'rgb' ```

Can't find a way to check image file type.

10

Can't find a safe way to get image file type, e.g jpg, png, bmp or other type. I tried get metadata with ```pyvips.Image.get_fields``` and ```pyvips.Image.get("vips_loader")```， but worried about its reliablity.

sharpen doesn't work with vips8.8.1

4

After scaled an image with resize, I used sharpen(sigma=0.5, x1=1, y2=10, y3=20, m1=0, m2=3 ), but nothing changed. `python: 3.6.8` `libvips: 8.8.1` ``` resized_image = pyvips.Image.resize(new_image, 0.2718, kernel="VIPS_KERNEL_LANCZOS3") sharpen_img =...

Congratulations you guys make a big progress in deep learning nerual nets. I found an interesting thing in the model initialization, the diff is so large when BN module initialized...

This script convert the label to anther, and only used when decompose face in `Datasetloader`. It seems no helpness with training. Any suggestion is appreciated.