https://www.kaggle.com/pierrenicolaspiquin/oct-segmentation/data # Settings ... otypes=[np.float]) def create_dataset(paths): x = [] y = [] for path in ...
In order to perform semantic segmentation, a higher level understanding of the image is required. The algorithm should figure out the objects present and also ...
10.01.2021 · Dataset Overview. The Semantic Drone Dataset focuses on semantic understanding of urban scenes for increasing the safety of autonomous drone flight and landing procedures. The imagery depicts more than 20 houses from nadir (bird's eye) view acquired at an altitude of 5 to 30 meters above ground. A high resolution camera was used to acquire ...
Let's perform semantic segmentation on this CARLA dataset using transfer learning. For ease of use, we'll begin by moving all the provided data into two ...
Jan 10, 2021 · The Semantic Drone Dataset focuses on semantic understanding of urban scenes for increasing the safety of autonomous drone flight and landing procedures. The imagery depicts more than 20 houses from nadir (bird's eye) view acquired at an altitude of 5 to 30 meters above ground. A high resolution camera was used to acquire images at a size of ...
MT19096. Mehmet Can Özkülekçi. Gleb Mischenko. Close. Report notebook. This Notebook is being promoted in a way I feel is spammy. Notebook contains abusive content that is not suitable for this platform. Plagiarism/copied content that is not meaningfully different. Votes for this Notebook are being manipulated.
29.05.2020 · The dataset consists of aerial imagery of Dubai obtained by MBRSC satellites and annotated with pixel-wise semantic segmentation in 6 classes. The total volume of the dataset is 72 images grouped into 6 larger tiles. The classes …
A Large Scale Fish Dataset ... Silver. more_horiz. SIIM ACR Pneumothorax Segmentation Data ... more_horiz. Semantic Segmentation for Self Driving Cars.
This dataset provides data images and labeled semantic segmentations captured via CARLA self-driving car simulator. The data was generated as part of the Lyft Udacity Challenge . This dataset can be used to train ML algorithms to identify semantic segmentation of cars, roads etc in an image. The data has 5 sets of 1000 images and corresponding ...
MT19096. Mehmet Can Özkülekçi. Gleb Mischenko. Close. Report notebook. This Notebook is being promoted in a way I feel is spammy. Notebook contains abusive content that is not suitable for this platform. Plagiarism/copied content that is not meaningfully different. Votes for this Notebook are being manipulated.
May 29, 2020 · The dataset consists of aerial imagery of Dubai obtained by MBRSC satellites and annotated with pixel-wise semantic segmentation in 6 classes. The total volume of the dataset is 72 images grouped into 6 larger tiles. The classes are: Building: #3C1098. Land (unpaved area): #8429F6.