From d5ee6e9533246c92d64a60a7c81fe2d53124674c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Rapha=C3=ABl=20Delhome?= Date: Thu, 14 May 2020 13:33:55 +0200 Subject: [PATCH] packaging: fix image URLs (use 'raw' instead of 'blob') --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index bd6454d..dc6106c 100644 --- a/README.md +++ b/README.md @@ -108,7 +108,7 @@ model test purpose, it does not contain filtered versions of images. The raw dataset contains 66 labels, splitted into 13 categories. The following figure depicts a prediction result over the 13-labelled dataset version. -![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/blob/master/images/mapillary_prediction_example.png) +![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/raw/master/images/mapillary_prediction_example.png) ## AerialImage (Inria) @@ -122,7 +122,7 @@ testing. Each of these images are 5000*5000 `tif` images. Amongst the 180 training images, we assigned 15 training images to validation. One example of this image from this dataset is depicted below. -![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/blob/master/images/aerial_prediction_example.png) +![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/raw/master/images/aerial_prediction_example.png) ## Open AI Tanzania @@ -137,7 +137,7 @@ allowing a fine data preprocessing step. In such a dataset, one tries to automatically detect building footprints by distinguishing complete buildings, incomplete buildings and foudations. -![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/blob/master/images/tanzania_prediction_example.png) +![Example of image, with labels and predictions](https://github.com/Oslandia/deeposlandia/raw/master/images/tanzania_prediction_example.png) ## Shapes