init comit

Dockerfile

+FROM arm64v8/ubuntu:18.04
+WORKDIR /home
+RUN : \
+    && apt-get update \
+    && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
+        software-properties-common \
+    && add-apt-repository -y ppa:deadsnakes \
+    && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
+        python3.8-venv \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/* \
+    && :
+RUN apt-get update && apt-get install apt-file -y && apt-file update && apt-get install vim -y
+RUN apt-get update && apt-get install ffmpeg libsm6 libxext6  -y
+RUN python3.8 -m venv /venv
+ENV PATH=/venv/bin:$PATH
+RUN python3 -V
+RUN python3 --version
+RUN python3 -m pip install --upgrade bosdyn-client bosdyn-mission bosdyn-choreography-client
+RUN python3 -m pip list --format=columns | grep bosdyn
+COPY requirements.txt .
+COPY setup_data_format.bash .
+COPY data_collection.py .
+RUN python3 -m pip install -r requirements.txt
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data_collection.py

+import argparse
+import sys
+import logging
+import time
+
+import cv2
+import numpy as np
+from datetime import datetime
+
+import bosdyn.client
+import bosdyn.client.util
+import bosdyn.client.math_helpers as math_helpers
+from bosdyn.api import image_pb2
+from bosdyn.client.image import ImageClient, build_image_request
+from bosdyn.client.graph_nav import GraphNavClient
+
+LOGGER = logging.getLogger()
+
+# data capture setup for navigation using AutoWalk 
+class DataCapture():
+    def __init__(self, robot): 
+        self.image_client = robot.ensure_client(
+            ImageClient.default_service_name)
+        self.graph_nav_client = robot.ensure_client(
+            GraphNavClient.default_service_name)
+
+    def start(self, options):
+        opt = options
+        # define cameras you want to capture from
+        image_request = [
+            build_image_request(source, pixel_format=format)
+            for source, format in [
+                ("back_depth",  "PIXEL_FORMAT_DEPTH_U16"),
+                ("back_fisheye_image", "PIXEL_FORMAT_RGB_U8"),
+                ("frontleft_depth", "PIXEL_FORMAT_DEPTH_U16"),
+                ("frontleft_fisheye_image", 'PIXEL_FORMAT_RGB_U8'),
+                ("frontright_depth", "PIXEL_FORMAT_DEPTH_U16" ),
+                ("frontright_fisheye_image", "PIXEL_FORMAT_RGB_U8"),
+                ("left_depth", "PIXEL_FORMAT_DEPTH_U16"),
+                ("left_fisheye_image", "PIXEL_FORMAT_RGB_U8"),
+                ("right_depth", "PIXEL_FORMAT_DEPTH_U16"),
+                ("right_fisheye_image", "PIXEL_FORMAT_RGB_U8")]
+        ]
+
+        while True:
+            image_responses = self.image_client.get_image(image_request)
+            state = self.graph_nav_client.get_localization_state()
+            print('saving data...')
+            self.save_images(image_responses, opt.output_path)
+            self.save_localisation(state, opt.output_path)
+
+    def save_localisation(self, state, output_path):
+        gn_origin_tform_body = state.localization.seed_tform_body
+        time_s = state.localization.timestamp.seconds
+        time_n = state.localization.timestamp.nanos
+        image_time = time_s + time_n / pow(10, 9)
+        pose = math_helpers.SE3Pose.from_obj(gn_origin_tform_body)
+        pose = pose.to_matrix()
+        with open(f"{output_path}/poses/{image_time}.json", "w") as f:
+            print(pose, file=f)
+
+    def save_images(self, images, output_path):
+        # byte encodings are provided by BD
+        for image in images:
+            num_bytes = 1
+            if image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_DEPTH_U16:
+                dtype = np.uint16
+                extension = ".png"
+            else:
+                if image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_RGB_U8:
+                    num_bytes = 3
+                elif image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_RGBA_U8:
+                    num_bytes = 4
+                elif image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_GREYSCALE_U8:
+                    num_bytes = 1
+                elif image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_GREYSCALE_U16:
+                    num_bytes = 2
+                dtype = np.uint8
+                extension = ".jpg"
+
+            img = np.frombuffer(image.shot.image.data, dtype=dtype)
+            if image.shot.image.format == image_pb2.Image.FORMAT_RAW:
+                try:
+                    # attempt to reshape array into a RGB rows X cols shape.
+                    img = img.reshape(
+                        (image.shot.image.rows, image.shot.image.cols, num_bytes))
+                except ValueError:
+                    # unable to reshape the image data, trying a regular decode.
+                    img = cv2.imdecode(img, -1)
+            elif image.shot.image.pixel_format == image_pb2.Image.PIXEL_FORMAT_DEPTH_U16:
+                cv_depth = np.frombuffer(image.shot.image.data, dtype=np.uint16)
+                cv_depth = cv_depth.reshape(image.shot.image.rows,
+                                            image.shot.image.cols)
+                img = cv_depth
+            else:
+                img = cv2.imdecode(img, -1)
+
+            image_time = image.shot.acquisition_time.seconds + image.shot.acquisition_time.nanos / pow(10, 9)
+            image_saved_path = image.source.name
+            image_saved_path = image_saved_path.replace("/", '')
+            cv2.imwrite(f'{output_path}/images/{image_saved_path}/' +
+                       image_saved_path + '_' + str(image_time) + extension, img)
+
+
+def main(argv):
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--output_path',
+                        help='path you output data to')
+    bosdyn.client.util.add_base_arguments(parser)
+    options = parser.parse_args(argv)
+
+    sdk = bosdyn.client.create_standard_sdk('data_capture')
+    robot = sdk.create_robot(options.hostname)
+    bosdyn.client.util.authenticate(robot)
+    robot.sync_with_directory()
+    robot.time_sync.wait_for_sync()
+
+    img_capture = DataCapture(robot)
+    # you'll manually have to kill this when you're ready for 
+    # collection to stop
+    img_capture.start(options)
+
+if __name__ == "__main__":
+    if not main(sys.argv[1:]):
+        sys.exit(1)
+

requirements.txt

+opencv-python >= 3.4.2.17
+numpy >= 1.16.4
+scipy>=1.3.1

setup_data_format.bash

+#!/bin/bash
+DEVICE_MOUNT=/data-collection
+SCENE_NAME=$1
+SEQUENCE_RUN=$2
+
+cd $DEVICE_MOUNT
+pwd
+mkdir -p "${SCENE_NAME}"
+cd "${SCENE_NAME}"
+pwd
+mkdir -p "sequence_${SEQUENCE_RUN}"
+cd "sequence_${SEQUENCE_RUN}"
+pwd
+mkdir -p images poses
+cd images
+pwd
+mkdir -p back_depth back_fisheye_image frontleft_depth frontleft_fisheye_image frontright_depth frontright_fisheye_image left_depth left_fisheye_image right_depth right_fisheye_image
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