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updated docs
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dusty-nv committed Jul 15, 2020
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21 changes: 11 additions & 10 deletions CHANGELOG.md
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Expand Up @@ -10,31 +10,32 @@ Major updates and new features to this project will be listed in this document.
* [Re-training SSD-Mobilenet](docs/pytorch-ssd.md) Object Detection tutorial with PyTorch
* Support for collection of object detection datasets and bounding-box labeling in `camera-capture` tool
* [`videoSource`](docs/aux-streaming.md) and [`videoOutput`](docs/aux-streaming.md) APIs for C++/Python that supports multiple types of video streams:
* MIPI CSI cameras
* V4L2 cameras
* RTP / RTSP
* Video & Images
* Image sequences
* OpenGL windows
* [`videoSource`](docs/aux-streaming.md#source-code) and [`videoOutput`](docs/aux-streaming.md#source-code) APIs for C++/Python that supports multiple types of video streams:
* [MIPI CSI cameras](docs/aux-streaming.md#mipi-csi-cameras)
* [V4L2 cameras](docs/aux-streaming.md#v4l2-cameras)
* [RTP](docs/aux-streaming.md#rtp) / [RTSP](docs/aux-streaming.md#rtsp)
* [Videos](docs/aux-streaming.md#video-files) & [Images](docs/aux-streaming.md#image-files)
* [Image sequences](docs/aux-streaming.md#image-files)
* [OpenGL windows](docs/aux-streaming.md#output-streams)
* Unified the `-console` and `-camera` samples to process both images and video streams
* [`imagenet.cpp`](examples/imagenet/imagenet.cpp) / [`imagenet.py`](python/examples/imagenet.py)
* [`detectnet.cpp`](examples/detectnet/detectnet.cpp) / [`detectnet.py`](python/examples/detectnet.py)
* [`segnet.cpp`](examples/segnet/segnet.cpp) / [`segnet.py`](python/examples/segnet-console.py)
* [`segnet.cpp`](examples/segnet/segnet.cpp) / [`segnet.py`](python/examples/segnet.py)
* Support for `uchar3/uchar4/float3/float4` images (default is now `uchar3` as opposed to `float4`)
* Replaced opaque Python image capsule with [`jetson.utils.cudaImage`](docs/aux-image.md#image-capsules-in-python) object
* Replaced opaque Python memory capsule with [`jetson.utils.cudaImage`](docs/aux-image.md#image-capsules-in-python) object
* See [Image Capsules in Python](docs/aux-image.md#image-capsules-in-python) for more info
* Images are now subscriptable/indexable from Python to directly access the pixel dataset
* Numpy ndarray conversion now supports `uchar3/uchar4/float3/float4` formats
* [`cudaConvertColor()`](https://github.com/dusty-nv/jetson-utils/blob/a587c20ad95d71efd47f9c91e3fbf703ad48644d/cuda/cudaColorspace.h#L31) automated colorspace conversion function (RGB, BGR, YUV, Bayer, grayscale, ect)
* Python CUDA bindings for `cudaResize()`, `cudaCrop()`, `cudaNormalize()`, `cudaOverlay()`
* See [Image Manipulation with CUDA](docs/aux-image.md) and [`cuda-examples.py`](https://github.com/dusty-nv/jetson-utils/blob/master/python/examples/cuda-examples.py) for examples of using these
* Transitioned to using Python3 by default since Python 2.7 is now past EOL
* DIGITS tutorial is now marked as deprecated (replaced by PyTorch transfer learning tutorial)
* Logging can now be controlled/disabled from the command line (e.g. `--log-level=verbose`)

## October 3, 2019

* Added new FCN-ResNet18 semantic segmentation models:
* Added new pre-trained FCN-ResNet18 semantic segmentation models:

| Dataset | Resolution | CLI Argument | Accuracy | Jetson Nano | Jetson Xavier |
|:------------:|:----------:|--------------|:--------:|:-----------:|:-------------:|
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -98,7 +98,7 @@ Additional C++ and Python samples for running the networks on static images and
|-------------------|---------------------|---------------------|
|    Image Recognition | [`imagenet.cpp`](examples/imagenet/imagenet.cpp) | [`imagenet.py`](python/examples/imagenet.py) |
|    Object Detection | [`detectnet.cpp`](examples/detectnet/detectnet.cpp) | [`detectnet.py`](python/examples/detectnet.py) |
|    Segmentation | [`segnet.cpp`](examples/segnet/segnet.cpp) | [`segnet.py`](python/examples/segnet-console.py) |
|    Segmentation | [`segnet.cpp`](examples/segnet/segnet.cpp) | [`segnet.py`](python/examples/segnet.py) |

> **note**: for working with numpy arrays, see [Converting to Numpy Arrays](docs/aux-image.md#converting-to-numpy-arrays) and [Converting from Numpy Arrays](docs/aux-image.md#converting-from-numpy-arrays)
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