From 294675ab58ba9ad8ca84734763f607a4d5e3fd45 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Miguel=20M=C3=A9ndez?= Date: Tue, 7 Sep 2021 09:17:37 +0200 Subject: [PATCH 1/2] Fix broken release link in README --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e80c2c9..24e5041 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ pip install pyodi ## Usage -Pyodi includes different applications that can help you to extract the most from your dataset. You can download our `TINY_COCO_ANIMAL` dataset from the [releases page](https://github.com/Gradiant/pyodi/releases/tag/v0.1.0) in order to test the example commands. A classic flow could follow the following steps: +Pyodi includes different applications that can help you to extract the most from your dataset. You can download our `TINY_COCO_ANIMAL` dataset from the [releases page](https://github.com/Gradiant/pyodi/releases/tag/v0.0.1) in order to test the example commands. A classic flow could follow the following steps: ### 1. Annotation visualization From addb20b2c36a47c0a029140d42d224abacf4eb4a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Miguel=20M=C3=A9ndez?= Date: Tue, 7 Sep 2021 09:26:06 +0200 Subject: [PATCH 2/2] Directly link dataset in Readme --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 24e5041..9cb7be4 100644 --- a/README.md +++ b/README.md @@ -54,7 +54,7 @@ pip install pyodi ## Usage -Pyodi includes different applications that can help you to extract the most from your dataset. You can download our `TINY_COCO_ANIMAL` dataset from the [releases page](https://github.com/Gradiant/pyodi/releases/tag/v0.0.1) in order to test the example commands. A classic flow could follow the following steps: +Pyodi includes different applications that can help you to extract the most from your dataset. You can download our `TINY_COCO_ANIMAL` dataset [here](https://github.com/Gradiant/pyodi/releases/download/v0.0.1/TINY_COCO_ANIMAL.zip) in order to test the example commands. A classic flow could follow the following steps: ### 1. Annotation visualization