From 07c1716c316eb9e7a9f41dd3c8d560a2a740cb63 Mon Sep 17 00:00:00 2001 From: Douglas De Rizzo Meneghetti Date: Tue, 12 Feb 2019 14:50:51 -0200 Subject: [PATCH 1/3] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 7ea188e..7faef37 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ The package works in two steps. First, it detects objects by using a video feed Object detection is done via the [dodo detector](https://github.com/douglasrizzo/dodo_detector) package. In case the single-shot detector is to be used, point the `inference_graph` and `label_map` parameters to your corresponding files. These files are created when training an object detection neural network using [TensorFlow Object Detection API](https://github.com/tensorflow/models/tree/master/research/object_detection). Also, the `ssd_confidence` parameter can be changed to adjust the detection threshold of the network. -In case the keypoint-based detector is to be used (either SIFT or RootSIFT), you need to create a database directory. The procedure to do so is described [here](http://dodo-detector.douglasrizzo.com.br/#keypoint-based-detector). +In case the keypoint-based detector is to be used (either SIFT or RootSIFT), you need to create a database directory. The procedure to do so is described [here](https://douglasrizzo.github.io/dodo_detector/#keypoint-based-detector). Edit `config/main_config.yaml` to select which type of detector you want as well as to point the package to the artifacts each detector expects. From 2e1e010de2b19aa13796b6ba669858d83e44b02d Mon Sep 17 00:00:00 2001 From: Douglas De Rizzo Meneghetti Date: Tue, 12 Feb 2019 14:51:12 -0200 Subject: [PATCH 2/3] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 7faef37..0b45823 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ This package makes information regarding detected objects available in a topic, When using an OpenNI-compatible sensor (like Kinect) the package uses point cloud information to locate objects in the world, wrt. to the sensor. -Click the image below for a YouTube vudeo showcasing the package at work. +Click the image below for a YouTube video showcasing the package at work. [![Youtube video](https://img.youtube.com/vi/fXJYmJOaSxQ/0.jpg)](https://www.youtube.com/watch?v=fXJYmJOaSxQ) From 082a93ff394db1a8d20e375a71554de0e2d7955c Mon Sep 17 00:00:00 2001 From: Douglas De Rizzo Meneghetti Date: Fri, 22 Mar 2019 18:46:52 -0300 Subject: [PATCH 3/3] changes to conform with dodo_detector 0.6 --- LICENSE | 2 +- package.xml | 2 +- src/detector.py | 4 ++-- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/LICENSE b/LICENSE index 398e242..5a7951c 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ BSD 3-Clause License -Copyright (c) 2018, Douglas De Rizzo Meneghetti +Copyright (c) 2019, Douglas De Rizzo Meneghetti All rights reserved. Redistribution and use in source and binary forms, with or without diff --git a/package.xml b/package.xml index 2d808db..24cc32a 100644 --- a/package.xml +++ b/package.xml @@ -1,7 +1,7 @@ dodo_detector_ros - 0.2.0 + 0.2.1 A package for object detection and localization using computer vision and IR sensors. diff --git a/src/detector.py b/src/detector.py index 4b574e2..50d3b91 100644 --- a/src/detector.py +++ b/src/detector.py @@ -143,9 +143,9 @@ def run(self): rospy.logdebug('Found ' + str(len(objects[obj_class])) + ' object(s) of type ' + obj_class) for obj_type_index, coordinates in enumerate(objects[obj_class]): - rospy.logdebug('...' + obj_class + ' ' + str(obj_type_index) + ' at ' + str(coordinates)) + rospy.logdebug('...' + obj_class + ' ' + str(obj_type_index) + ' at ' + str(coordinates['box'])) - ymin, xmin, ymax, xmax = coordinates + ymin, xmin, ymax, xmax = coordinates['box'] y_center = ymax - ((ymax - ymin) / 2) x_center = xmax - ((xmax - xmin) / 2)