MICCAI Challenge 2019 Dataset
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About
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There are 3 datasets (which are all from different pigs) each containing 5 keyframes. Keyframes are all single captures with a unique positioning of the endoscope and several positions of the structured light illuminator. The keyframes (with the exception of the last keyframe in each dataset) have additional data from interpolation using the camera kinematics to 'warp' the depth images to the new camera coordinates. These warped depth maps could be computed yourself manually since we provide the camera transforms but we are providing them for your convenience. Please do not assume they are perfect ground truth, due to errors in the kinematics or synchronization issues between the camera and video stream, there will be small errors in the warped vertex positions. 

Each keyframe should contain the following files
* `camera_calibration.yaml` This is an approximate calibration of the endoscope and may be inaccurate. It is in OpenCV format and you can load this data directly using OpenCV `FileStorage` class. However, depth estimation methods are expected to be robust to errors in camera calibration.
* `Left_Image.png` This is the left camera view used when the structured light patterns for keyframe `N` were captured.
* `Right_Image.png` This is the right camera view.
* `left_depth_map.tiff` This is the point cloud as seen by the left camera. Each pixel in the `.tiff` file contains an `(X,Y,Z)` coordinate which is the vertex position in left camera space that the pixel projects to.
* `right_depth_map.tiff` This is the point cloud as seen by the right camera.
* `point_cloud.obj` This is a 3D vertex model you can load into software such as `blender` or `meshlab` to view the coordinates.
* `data/rgb.mp4` This is the sequence of video frames (stacked left above right) that we captured after the structured light sequence for keyframe `N`. You should be able to open and decode this file with either OpenCV or ffmpeg. Standard video players (vlc/quicktime/wmp) may not work.
* `data/frame_data.tar.gz` This is a archive of frames with the naming format `frame_data%06d.json`. Each `frame_data` corresponds to a single video frame where the number in the file name can be used for matching. The frame data consists of the camera transform relative to the camera position where the keyframe illuminator image was captured (`Left_Image.png`/`Right_Image.png`) and the camera calibration data for that frame.
* `data/scene_points.tar.gz` This is a archive of `.tiff` files with the naming format `scene_points%06d.tiff`. Like the `frame_data` files above, each `scene_points` corresponds to a single video frame where the number in the file name can be used for matching. The `.tiff` files contain the vertex coordinates warped from the keyframe illuminator image. Please note that as the camera motion introduces new pixels which are not captured in the illuminator scene, these pixels do not have an associated ground truth depth. You can find these pixels as they contain the value set `(0,0,0)` in the `.tiff` file. 


Helpful Notes
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* Opening `.tiff` files can be performed with the Python library `tifffile` which is installable with `pip`. This format allow the storage of floating point images. 
* We apologize that interpolation is missing for `dataset_1/keyframe_4` is missing. This was due to a logging error.