0.0.1, detection

README.md

@@ -1,2 +1,46 @@
 # edgeimpulse_ros
 ROS2 wrapper for Edge Impulse 
+
+
+## How to install
+
+1. install edge_impulse_linux: <br>
+    `pip3 install edge_impulse_linux`
+
+2. on some boards and aarch64 these are required (e.g. vm on mac m1): <br>
+    `sudo apt-get install libatlas-base-dev libportaudio2 libportaudiocpp0 portaudio19-dev` <br>
+    `pip3 install pyaudio` <br>
+
+3. download your .eim file as **"linux board"** and choose your architecture
+
+4. make your eim file as executable: <br>
+    `cd /path/to/your/eim/file` <br>
+    `chmod +x <file>.eim` <br>
+
+5. clone this repo in your workspace: <br>
+    `cd ~/dev_ws/src`
+    `git clone https://github.com/gbr1/edgeimpulse_ros`
+
+6. check dependencies: <br>
+    `cd ~/dev_ws` <br>
+    `rosdep install --from-paths src --ignore-src -r -y` <br>
+
+7. build: <br>
+    `colcon build --symlink-install` <br>
+    `source install/setup.bash` <br>
+
+
+## How to run
+
+Launch the node: <br>
+    `ros2 run edgeimpulse_ros image_classification --ros-args -p model.filepath:="</absolute/path/to/your/eim/file.eim>" -r /detection/input/image:="/your_image_topic"`
+` <br>
+
+
+
+***Copyright © 2022 Giovanni di Dio Bruno - gbr1.github.io***
+
+
+
+
+

edgeimpulse_ros/image_classification.py

@@ -0,0 +1,182 @@
+# Copyright 2022 Giovanni di Dio Bruno - gbr1.github.io
+
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+
+#     http://www.apache.org/licenses/LICENSE-2.0
+
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+
+from unittest import result
+from .submodules import device_patches
+import cv2
+
+import rclpy
+from rclpy.node import Node
+
+from cv_bridge import CvBridge
+
+from sensor_msgs.msg import Image
+
+#from vision_msgs.msg import BoundingBox2DArray
+#from vision_msgs.msg import VisionInfo
+
+import os
+import time
+import sys, getopt
+import numpy as np
+from edge_impulse_linux.image import ImageImpulseRunner
+
+
+
+class EI_Image_node(Node):
+    def __init__(self):
+
+        self.occupied = False
+        self.img = None
+        self.cv_bridge = CvBridge()
+
+        super().__init__('ei_image_classifier_node')
+        self.init_parameters()
+        self.ei_classifier = self.EI_Classifier(self.modelfile, self.get_logger())
+        #self.publisher = self.create_publisher(BoundingBox2DArray,'/edge_impulse/detection',1)
+
+        self.timer_parameter = self.create_timer(2,self.parameters_callback)
+
+        self.image_publisher = self.create_publisher(Image,'/detection/output/image',1)
+        self.timer_classify = self.create_timer(0.01,self.classify_callback)
+        self.timer_classify.cancel()
+        self.subscription = self.create_subscription(Image,'/detection/input/image',self.listener_callback,1)
+        self.subscription 
+
+
+    def init_parameters(self):
+        self.declare_parameter('model.filepath','')
+        self.modelfile= self.get_parameter('model.filepath').get_parameter_value().string_value
+
+        self.declare_parameter('show.overlay', True)
+        self.show_overlay = self.get_parameter('show.overlay').get_parameter_value().bool_value
+
+        self.declare_parameter('show.labels',True)
+        self.show_labels_on_image = self.get_parameter('show.labels').get_parameter_value().bool_value
+
+        self.declare_parameter('show.classification_info', False)
+        self.show_extra_classification_info = self.get_parameter('show.classification_info').get_parameter_value().bool_value
+
+
+
+
+
+
+
+    def parameters_callback(self):
+        self.show_labels_on_image = self.get_parameter('show.labels').get_parameter_value().bool_value
+        self.show_extra_classification_info = self.get_parameter('show.classification_info').get_parameter_value().bool_value
+        self.show_overlay = self.get_parameter('show.overlay').get_parameter_value().bool_value
+
+
+
+
+    def listener_callback(self, msg):
+        if len(msg.data):
+            current_frame = self.cv_bridge.imgmsg_to_cv2(msg)
+            current_frame = cv2.cvtColor(current_frame, cv2.COLOR_BGR2RGB)
+            if not self.occupied:
+                self.img = current_frame
+                self.timer_classify.reset()
+
+    def classify_callback(self):
+        self.occupied = True
+
+        # classify
+        features, cropped, res = self.ei_classifier.classify(self.img)
+
+        #prepare output
+        if "classification" in res["result"].keys():
+            if self.show_extra_classification_info:
+                self.get_logger().info('Result (%d ms.) ' % (res['timing']['dsp'] + res['timing']['classification']), end='')
+            for label in self.labels:
+                score = res['result']['classification'][label]
+                if self.show_extra_classification_info:
+                    self.get_logger().info('%s: %.2f\t' % (label, score), end='')
+
+
+        elif "bounding_boxes" in res["result"].keys():
+            if self.show_extra_classification_info:
+                self.get_logger().info('Found %d bounding boxes (%d ms.)' % (len(res["result"]["bounding_boxes"]), res['timing']['dsp'] + res['timing']['classification']))
+
+            for bb in res["result"]["bounding_boxes"]:
+                if self.show_extra_classification_info:
+                    self.get_logger().info('%s (%.2f): x=%d y=%d w=%d h=%d' % (bb['label'], bb['value'], bb['x'], bb['y'], bb['width'], bb['height']))
+                if self.show_overlay:
+                    img_res = cv2.rectangle(cropped, (bb['x'], bb['y']), (bb['x'] + bb['width'], bb['y'] + bb['height']), (255, 0, 0), 1)
+                    if self.show_labels_on_image:
+                        composed_label = bb['label']+' '+str(round(bb['value'],2))
+                        img_res = cv2.putText(img_res, composed_label, (bb['x'], bb['y']-5), cv2.FONT_HERSHEY_SIMPLEX, 0.4, (255,0,0),1)
+
+        cropped=cv2.cvtColor(cropped, cv2.COLOR_RGB2BGR)
+
+        # publish message
+        self.image_publisher.publish(self.cv_bridge.cv2_to_imgmsg(cropped,"bgr8"))
+
+        self.occupied= False
+        self.timer_classify.cancel()
+
+
+    class EI_Classifier:
+        def __init__(self, modelfile, logger):
+            self.runner = None
+            self.labels = None
+            self.logger = logger
+            with ImageImpulseRunner(modelfile) as self.runner:
+                try:
+                    self.model_info = self.runner.init()
+                    #print(self.model_info)
+                    self.logger.info('Model loaded successfully!')
+                    self.logger.info('Model owner: '+ self.model_info['project']['owner'])
+                    self.logger.info('Model name: ' + self.model_info['project']['name'])
+                    self.logger.info('Model version: ' + str(self.model_info['project']['deploy_version']))
+                    self.logger.info('Model type: '+ self.model_info['model_parameters']['model_type'])
+                    self.labels = self.model_info['model_parameters']['labels']
+
+                except:
+                    self.logger.error('Issue on opening .eim file')
+                    if (self.runner):
+                        self.runner.stop()
+
+
+        def __del__(self):
+            if (self.runner):
+                self.runner.stop()  
+
+        def classify(self, img):
+            try:
+                # classification
+                features, cropped = self.runner.get_features_from_image(img)
+                res = self.runner.classify(features)
+                return features, cropped, res
+            except:
+                # somenthing went wrong >_<
+                self.logger.error('Error on classification')
+
+
+def main():
+    rclpy.init()
+    node = EI_Image_node()
+    rclpy.spin(node)
+
+    node.destroy_node()
+    rclpy.shutdown()
+
+
+if __name__ == "__main__":
+   main()
+
+
+

edgeimpulse_ros/submodules/device_patches.py

@@ -0,0 +1,15 @@
+import os
+
+def get_device():
+    # On Jetson Nano `OPENBLAS_CORETYPE=ARMV8` needs to be set, otherwise including OpenCV
+    # throws an illegal instruction error
+    if (os.path.exists('/proc/device-tree/model')):
+        with open('/proc/device-tree/model', 'r') as f:
+            model = f.read()
+            if ('NVIDIA Jetson Nano' in model):
+                return 'jetson-nano'
+    return 'unknown'
+
+device = get_device()
+if (device == 'jetson-nano'):
+    os.environ['OPENBLAS_CORETYPE'] = 'ARMV8'

package.xml

@@ -0,0 +1,24 @@
+<?xml version="1.0"?>
+<?xml-model href="http://download.ros.org/schema/package_format3.xsd" schematypens="http://www.w3.org/2001/XMLSchema"?>
+<package format="3">
+  <name>edgeimpulse_ros</name>
+  <version>0.0.1</version>
+  <description>ROS2 wrapper for Edge Impulse</description>
+  <maintainer email="[email protected]">gbr1</maintainer>
+  <license>Apache 2.0</license>
+
+  <depend>vision_opencv</depend>
+
+  <test_depend>ament_copyright</test_depend>
+  <test_depend>ament_flake8</test_depend>
+  <test_depend>ament_pep257</test_depend>
+  <test_depend>python3-pytest</test_depend>
+
+  <!--<exec_depend>vision_msgs</exec_depend>-->
+  <exec_depend>sensor_msgs</exec_depend>
+  <exec_depend>ros2launch</exec_depend>
+
+  <export>
+    <build_type>ament_python</build_type>
+  </export>
+</package>

setup.cfg

@@ -0,0 +1,4 @@
+[develop]
+script-dir=$base/lib/edgeimpulse_ros
+[install]
+install-scripts=$base/lib/edgeimpulse_ros

setup.py

@@ -0,0 +1,26 @@
+from setuptools import setup
+
+package_name = 'edgeimpulse_ros'
+submodules = 'edgeimpulse_ros/submodules'
+setup(
+    name=package_name,
+    version='0.0.1',
+    packages=[package_name, submodules],
+    data_files=[
+        ('share/ament_index/resource_index/packages',
+            ['resource/' + package_name]),
+        ('share/' + package_name, ['package.xml']),
+    ],
+    install_requires=['setuptools'],
+    zip_safe=True,
+    maintainer='Giovanni di Dio Bruno',
+    maintainer_email='[email protected]',
+    description='ROS2 wrapper for Edge Impulse',
+    license='Apache 2.0',
+    tests_require=['pytest'],
+    entry_points={
+        'console_scripts': [
+            'image_classification = edgeimpulse_ros.image_classification:main'
+        ],
+    },
+)

test/test_copyright.py

@@ -0,0 +1,23 @@
+# Copyright 2015 Open Source Robotics Foundation, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from ament_copyright.main import main
+import pytest
+
+
+@pytest.mark.copyright
+@pytest.mark.linter
+def test_copyright():
+    rc = main(argv=['.', 'test'])
+    assert rc == 0, 'Found errors'

test/test_flake8.py

@@ -0,0 +1,25 @@
+# Copyright 2017 Open Source Robotics Foundation, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from ament_flake8.main import main_with_errors
+import pytest
+
+
+@pytest.mark.flake8
+@pytest.mark.linter
+def test_flake8():
+    rc, errors = main_with_errors(argv=[])
+    assert rc == 0, \
+        'Found %d code style errors / warnings:\n' % len(errors) + \
+        '\n'.join(errors)

test/test_pep257.py

@@ -0,0 +1,23 @@
+# Copyright 2015 Open Source Robotics Foundation, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from ament_pep257.main import main
+import pytest
+
+
+@pytest.mark.linter
+@pytest.mark.pep257
+def test_pep257():
+    rc = main(argv=['.', 'test'])
+    assert rc == 0, 'Found code style errors / warnings'