提交 f1fa36bf 编写于 作者: T Tomer Ashuach 提交者: Evgeni Raikhel

changed http links to https in readme and cmake files

change another link in doc/sample-data.md

fixed another link

changed more http to https links

(cherry picked from commit 23ad67d50d582c0c77cfeae91b2347628d5f8176)

Change-Id: Ib31a41d313406182530aa6acc243bade94b9987d
上级 898d6fcb
......@@ -63,7 +63,7 @@ build:
#
test_script:
- ps: >-
$url_records_path = "http://realsense-hw-public.s3.amazonaws.com/rs-tests/lrs_2.8.3/"
$url_records_path = "https://librealsense.intel.com/rs-tests/lrs_2.8.3/"
$url_records_list = $url_records_path + "records.txt"
......
......@@ -21,11 +21,11 @@ In case the public key still cannot be retrieved, check and specify proxy settin
- Add the server to the list of repositories:
Ubuntu 16 LTS:
`sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo xenial main" -u`
`sudo add-apt-repository "deb https://librealsense.intel.com/Debian/apt-repo xenial main" -u`
Ubuntu 18 LTS:
`sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo bionic main" -u`
`sudo add-apt-repository "deb https://librealsense.intel.com/Debian/apt-repo bionic main" -u`
Ubuntu 20 LTS:
`sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo focal main" -u`
`sudo add-apt-repository "deb https://librealsense.intel.com/Debian/apt-repo focal main" -u`
- Install the libraries (see section below if upgrading packages):
`sudo apt-get install librealsense2-dkms`
......
......@@ -54,12 +54,12 @@ Note that this method provides binary installation compiled using the `-DFORCE_R
* Ubuntu 16:
```
sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo xenial main" -u
sudo add-apt-repository "deb https://librealsense.intel.com/Debian/apt-repo xenial main" -u
```
* Ubuntu 18:
```
sudo add-apt-repository "deb http://realsense-hw-public.s3.amazonaws.com/Debian/apt-repo bionic main" -u
sudo add-apt-repository "deb https://librealsense.intel.com/Debian/apt-repo bionic main" -u
```
3. Install the SDK:
......
......@@ -18,8 +18,8 @@ pipe.start(cfg); // Load from file
| []() | []() |
| ------------- |---------------|
| <a href="http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/outdoors.bag" title="Outdoors Stereo Example">![](http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/outdoor-preview.png)</a> | Outdoors scene captured with D415 pre-production sample (Depth from Stereo) |
| <a href="http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/stairs.bag" title="Staircase Example">![](http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/stairs-preview.png)</a> | Flight of stairs captured D435 pre-production sample (Depth from Stereo) |
| <a href="http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/structured.bag" title="Structured Light Short-Range Example">![](http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/structured-preview.png)</a> | Short-range scene captured with the SR300 Depth Camera (Structured Light technology) |
| <a href="http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/depth_under_water.bag" title="D415 + Submerged objects">![](http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/depth_under_water.png)</a> | Scene captured with pre-production D415 device (Depth from Stereo) with objects submerged under water [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/IntelRealSense/librealsense/jupyter?filepath=notebooks/depth_under_water.ipynb) |
| <a href="http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/d435i_sample_data.zip" title="D435i_sample">![](http://realsense-hw-public.s3.amazonaws.com/rs-tests/TestData/d435i_preview.png)</a> | Outdoor scene with D435i pre-production sample (Depth from Stereo with IMU) |
| <a href="https://librealsense.intel.com/rs-tests/TestData/outdoors.bag" title="Outdoors Stereo Example">![](https://librealsense.intel.com/rs-tests/TestData/outdoor-preview.png)</a> | Outdoors scene captured with D415 pre-production sample (Depth from Stereo) |
| <a href="https://librealsense.intel.com/rs-tests/TestData/stairs.bag" title="Staircase Example">![](https://librealsense.intel.com/rs-tests/TestData/stairs-preview.png)</a> | Flight of stairs captured D435 pre-production sample (Depth from Stereo) |
| <a href="https://librealsense.intel.com/rs-tests/TestData/structured.bag" title="Structured Light Short-Range Example">![](https://librealsense.intel.com/rs-tests/TestData/structured-preview.png)</a> | Short-range scene captured with the SR300 Depth Camera (Structured Light technology) |
| <a href="https://librealsense.intel.com/rs-tests/TestData/depth_under_water.bag" title="D415 + Submerged objects">![](https://librealsense.intel.com/rs-tests/TestData/depth_under_water.png)</a> | Scene captured with pre-production D415 device (Depth from Stereo) with objects submerged under water [![Binder](https://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/IntelRealSense/librealsense/jupyter?filepath=notebooks/depth_under_water.ipynb) |
| <a href="https://librealsense.intel.com/rs-tests/TestData/d435i_sample_data.zip" title="D435i_sample">![](https://librealsense.intel.com/rs-tests/TestData/d435i_preview.png)</a> | Outdoor scene with D435i pre-production sample (Depth from Stereo with IMU) |
......@@ -164,7 +164,7 @@ endfunction()
set(PP_TESTS_URL https://librealsense.intel.com/rs-tests/post_processing_tests_2018_ww18/)
set(PP_TESTS_URL https://librealsense.intel.com/rs-tests/post_processing_tests_2018_ww18/)
message(STATUS "Preparing to download Post-processing tests dataset...\nRemote server: ${PP_TESTS_URL}\nTarget Location: ${Deployment_Location}\n")
foreach(i ${PP_Tests_List})
set(Test_Pattern ${i})
......@@ -209,7 +209,7 @@ list(APPEND PP_Rosbag_Recordings_List
single_depth_color_640x480.bag
D435i_Depth_and_IMU.bag
)
set(PP_Rosbag_Recordings_URL https://librealsense.intel.com/rs-tests/Rosbag_unit_test_records/)
set(PP_Rosbag_Recordings_URL https://librealsense.intel.com/rs-tests/Rosbag_unit_test_records/)
foreach(i ${PP_Rosbag_Recordings_List})
set (empty FALSE)
is_file_empty(empty, ${Deployment_Location}${i} )
......
# Image files are not included in our distribution. Define a function for easy downloading at CMake time:
#realsense-hw-public/rs-tests/algo/depth-to-rgb-calibration/19.2.20/F9440687/Snapshots/LongRange 768X1024 (RGB 1920X1080)
set(ALGO_SRC_URL "http://realsense-hw-public.s3-eu-west-1.amazonaws.com/rs-tests/algo")
set(ALGO_SRC_URL "https://librealsense.intel.com/rs-tests/algo")
function(dl_algo_file filename sha1)
set(path "${CMAKE_CURRENT_BINARY_DIR}/algo/${filename}")
......
......@@ -37,14 +37,14 @@ task downloadFirmware() {
def d4xxFile = new File("$projectDir/src/main/res/raw/fw_d4xx.bin")
if (!d4xxFile.exists()) {
println("downloading D4xx fw: " + d4xxFwVersion)
new URL('http://realsense-hw-public.s3-eu-west-1.amazonaws.com/Releases/RS4xx/FW/D4XX_FW_Image-' + d4xxFwVersion + '.bin').withInputStream{ i -> d4xxFile.withOutputStream{ it << i }}
new URL('https://librealsense.intel.com/Releases/RS4xx/FW/D4XX_FW_Image-' + d4xxFwVersion + '.bin').withInputStream{ i -> d4xxFile.withOutputStream{ it << i }}
}
def sr3xxFwVersion = getFwVersion('SR3XX_RECOMMENDED_FIRMWARE_VERSION')
def sr3xxFile = new File("$projectDir/src/main/res/raw/fw_sr3xx.bin")
if (!sr3xxFile.exists()) {
println("downloading SR3xx fw: " + sr3xxFwVersion)
new URL('http://realsense-hw-public.s3-eu-west-1.amazonaws.com/Releases/SR300/FW/SR3XX_FW_Image-' + sr3xxFwVersion + '.bin').withInputStream{ i -> sr3xxFile.withOutputStream{ it << i }}
new URL('https://librealsense.intel.com/Releases/SR300/FW/SR3XX_FW_Image-' + sr3xxFwVersion + '.bin').withInputStream{ i -> sr3xxFile.withOutputStream{ it << i }}
}
}
......
# Getting Started with RealSense™ SDK2.0 for LabVIEW®
> **Download Links**:
> * [**(Latest)** RealSense SDK2 for LabVIEW 1.0, 2.33.0, Feb 2020](https://realsense-hw-public.s3-eu-west-1.amazonaws.com/Releases/RS4xx/Windows/labview_2_33_0.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.11.0, May 2018](http://realsense-hw-public.s3.amazonaws.com/Releases/RS4xx/Windows/labview_2.11_0.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.10.4, Apr 2018](http://realsense-hw-public.s3.amazonaws.com/Releases/RS4xx/Windows/labview_2_10_4.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.8.1, Nov 2017](http://realsense-hw-public.s3.amazonaws.com/Releases/RS4xx/Windows/labview_2_8_1.zip)
> * [**(Latest)** RealSense SDK2 for LabVIEW 1.0, 2.33.0, Feb 2020](https://librealsense.intel.com/Releases/RS4xx/Windows/labview_2_33_0.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.11.0, May 2018](https://librealsense.intel.com/Releases/RS4xx/Windows/labview_2.11_0.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.10.4, Apr 2018](https://librealsense.intel.com/Releases/RS4xx/Windows/labview_2_10_4.zip)
> * [RealSense SDK2 for LabVIEW 1.0, 2.8.1, Nov 2017](https://librealsense.intel.com/Releases/RS4xx/Windows/labview_2_8_1.zip)
## Introduction:
The latest generation of RealSense Depth Cameras can be controlled via the RealSense SDK2.0, also referred to as libRealSense 2.x.x, or LibRS for short. This includes stereo depth cameras D415 and D435 as well as their corresponding modules, such as D410 and D430.
To get started controlling the RealSense Cameras with LabVIEW® in Windows 10, we have created a [VI-library](http://realsense-hw-public.s3.amazonaws.com/Releases/RS4xx/Windows/labview_2_8_1.zip) that wraps most of the core functions of the realsense2.dll, and we have also created some simple “Hello World” VI’s to get started capturing Color, Depth Maps, and displaying Point-Clouds. This uses LabVIEW 2016 and requires a Windows 10 laptop with a USB3 port.
To get started controlling the RealSense Cameras with LabVIEW® in Windows 10, we have created a [VI-library](https://librealsense.intel.com/Releases/RS4xx/Windows/labview_2_8_1.zip) that wraps most of the core functions of the realsense2.dll, and we have also created some simple “Hello World” VI’s to get started capturing Color, Depth Maps, and displaying Point-Clouds. This uses LabVIEW 2016 and requires a Windows 10 laptop with a USB3 port.
The realsense2.dll that is included in this package is 64bit for Windows 10. Other versions (ex: 32bit) could be compiled by following the [instructions on GitHub](https://github.com/IntelRealSense/librealsense/blob/master/doc/installation_windows.md). Just rename them realsense2.dll and replace the file in the location used by the LabVIEW demos.
......
# OpenVINO model files are not included in our distribution. Define a function for easy
# downloading at CMake time:
set(OPENVINO_MODEL_SRC_URL "http://realsense-hw-public.s3-eu-west-1.amazonaws.com/rs-tests/OpenVINO_data")
set(OPENVINO_MODEL_SRC_URL "https://librealsense.intel.com/rs-tests/OpenVINO_data")
function(dl_vino_model filename sha1)
set(path "${CMAKE_CURRENT_BINARY_DIR}/${filename}")
if(NOT EXISTS "${path}")
......
......@@ -211,7 +211,7 @@ When we upsample we get the lost information back (by the concatenation process)
so we can see last-layer features in the perspective of the layer above them.
#### Training Dataset
Download [part 1](http://realsense-hw-public.s3.eu-west-1.amazonaws.com/rs-tests/ML/Depth_Learning/Dataset/part1_1_4000.zip) and [part 2](http://realsense-hw-public.s3.eu-west-1.amazonaws.com/rs-tests/ML/Depth_Learning/Dataset/part2_4001_8375.zip) of the dataset. It contains 4 types of 848x480 images in uncompressed PNG format:
Download [part 1](https://librealsense.intel.com/rs-tests/ML/Depth_Learning/Dataset/part1_1_4000.zip) and [part 2](http://realsense-hw-public.s3.eu-west-1.amazonaws.com/rs-tests/ML/Depth_Learning/Dataset/part2_4001_8375.zip) of the dataset. It contains 4 types of 848x480 images in uncompressed PNG format:
###### 1. Simulated Left Infrared:
- Synthetic view from left infrared sensor of the virtual camera, including infrared projection pattern
......@@ -327,7 +327,7 @@ The output is a BAG file that could be opened by RealSense viewer.
## Part 5 - Applying trained network to real data:
[Example 5](https://github.com/nohayassin/librealsense/blob/tensorflow/wrappers/tensorflow/example5%20-%20denoise.py) is showing how to use trained network from Part 4 ([Keras Unet model](http://realsense-hw-public.s3.eu-west-1.amazonaws.com/rs-tests/ML/Depth_Learning/DEPTH_Keras_Unet.model.zip)) on live data from Intel RealSense Camera. It can be invoke as follows:
[Example 5](https://github.com/nohayassin/librealsense/blob/tensorflow/wrappers/tensorflow/example5%20-%20denoise.py) is showing how to use trained network from Part 4 ([Keras Unet model](https://librealsense.intel.com/rs-tests/ML/Depth_Learning/DEPTH_Keras_Unet.model.zip)) on live data from Intel RealSense Camera. It can be invoke as follows:
```py
python camera_simulation.py <path to the model>
......
# Unity Wrapper for RealSense SDK 2.0
<p align="center"><img src="http://realsense-hw-public.s3.amazonaws.com/rs-tests/unity_screenshot.PNG" height="400"/></p>
<p align="center"><img src="https://librealsense.intel.com/rs-tests/unity_screenshot.PNG" height="400"/></p>
> [Download **realsense.unitypackage**](https://github.com/IntelRealSense/librealsense/releases) and go to `Assets > Scenes > Start Here` to see the home screen above
......
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