tandpfun

REPO HERE: https://github.com/tandpfun/wardrobe

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name: extract-clothing-cutouts description: Extract high-quality, deduplicated transparent ecommerce clothing cutouts from a folder of photographs where people wear one or more garments. Use when Codex must find outfit or model photos, identify unique clothing across images, create focused references, reconstruct complete garments with Imagegen, remove a solid chroma background into RGBA PNGs, and output only the finished clothing images into a new folder under the current working directory.

Extract Clothing Cutouts

Turn photographs of worn clothing into source-faithful standalone catalog PNGs. Treat each result as a reconstruction from visible evidence, not literal segmentation whenever the wearer or another layer occludes part of the garment.

simont77

Elgato Eve HomeKit Services & Characteristics

A work in progress collection of proprietary and as of yet undocumented HomeKit characteristics and their UUIDs used by Elgato Eve.

Based on the work by gomfunkel and 0ff. Characteristics and data dump for Door, Motion and Thermo thanks to @NebzHB.

More infos not yet incorporated in the comment section.

This list is not including all Eve accessories available and some services and characteristics still make no sense to me. If you have anything to contribute, please leave a comment. There is no guarantee that the information listed below is correct.

flyyufelix

ResNet-152 in Keras

This is an Keras implementation of ResNet-152 with ImageNet pre-trained weights. I converted the weights from Caffe provided by the authors of the paper. The implementation supports both Theano and TensorFlow backends. Just in case you are curious about how the conversion is done, you can visit my blog post for more details.

ResNet Paper:

Deep Residual Learning for Image Recognition.
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
arXiv:1512.03385

kyledrake

# The blog post that started it all: https://neocities.org/blog/the-fcc-is-now-rate-limited
#
# Current known FCC address ranges:
# https://news.ycombinator.com/item?id=7716915
#
# Confirm/locate FCC IP ranges with this: http://whois.arin.net/rest/net/NET-165-135-0-0-1/pft
#
# In your nginx.conf:

location / {