From 3aaf498f11a69054c28f265c30bf0769c632ba92 Mon Sep 17 00:00:00 2001 From: david Date: Sun, 5 Jan 2025 21:21:10 -0700 Subject: [PATCH] spelling fixes 4 --- .wordlist.txt | 27 +++++++++++++++++++ ...-pollution-detection-arduino-nano-esp32.md | 2 +- .../robotic-arm-sorting-arduino-braccio.md | 4 +-- 3 files changed, 30 insertions(+), 3 deletions(-) diff --git a/.wordlist.txt b/.wordlist.txt index 5790e25..468d538 100644 --- a/.wordlist.txt +++ b/.wordlist.txt @@ -2155,6 +2155,7 @@ vcLQKY Roboflow SRDF OpenVINO’s +OpenVINO's oakd MRD oAxaV @@ -2166,4 +2167,30 @@ OpenAI's PRjhA jBE gnhUcwYqrI +RTU +shrimplets +TetrisBot +serv +pairplot +CLK +datacenter +Printables +Dall +overpredicting +Autotuning +RTU +shrimplets +TetrisBot +pairplot +CLK +datacenter +Printables +Autotuning +Powerstrip +Chardev +tera +HailoTracker +Roboflow’s +Lescaudron +ECR diff --git a/air-quality-and-environmental-projects/water-pollution-detection-arduino-nano-esp32.md b/air-quality-and-environmental-projects/water-pollution-detection-arduino-nano-esp32.md index e9b4ff2..be3437c 100644 --- a/air-quality-and-environmental-projects/water-pollution-detection-arduino-nano-esp32.md +++ b/air-quality-and-environmental-projects/water-pollution-detection-arduino-nano-esp32.md @@ -52,7 +52,7 @@ Even though this underwater air bubble and water pollution detection device is c Then, I employed the web application to communicate with UNIHIKER to generate a pre-formatted CSV file from the stored sample text files (ultrasonic scan data records) and transfer the latest neural network model detection result (ultrasonic scan buffer and the detected label) via an HTTP GET request. -As mentioned repeatedly, each generated ultrasonic scan buffer provides 400 data points as a 20 x 20 ultrasonic image despite the fact that Nano ESP32 cannot utilize the given buffer to produce an ultrasonic image after running the neural network model with the Ridge classifier. Therefore, after receiving the latest model detection result via the web application, I employed UNIKIHER to modify a template image (black square) via the built-in OpenCV functions to convert the given ultrasonic scan buffer to a JPG file and save the modified image to visualize the latest aquatic ultrasonic scan with thoroughly encoded pixels. +As mentioned repeatedly, each generated ultrasonic scan buffer provides 400 data points as a 20 x 20 ultrasonic image despite the fact that Nano ESP32 cannot utilize the given buffer to produce an ultrasonic image after running the neural network model with the Ridge classifier. Therefore, after receiving the latest model detection result via the web application, I employed UNIHIKER to modify a template image (black square) via the built-in OpenCV functions to convert the given ultrasonic scan buffer to a JPG file and save the modified image to visualize the latest aquatic ultrasonic scan with thoroughly encoded pixels. Since the RetinaNet object detection model provides accurate bounding box measurements, I also utilized UNIHIKER to modify the resulting images to draw the associated bounding boxes and save the modified resulting images as JPG files for further inspection. diff --git a/readme/featured-machine-learning-projects/robotic-arm-sorting-arduino-braccio.md b/readme/featured-machine-learning-projects/robotic-arm-sorting-arduino-braccio.md index d7531dd..6485e02 100644 --- a/readme/featured-machine-learning-projects/robotic-arm-sorting-arduino-braccio.md +++ b/readme/featured-machine-learning-projects/robotic-arm-sorting-arduino-braccio.md @@ -372,7 +372,7 @@ $ mo --model_name ei-pnp_yolov5n_320 \ --input_model ei-pnp_yolov5n_320_batch32_epoch100_prune.onnx ``` -After converting the model to OpenVINO’s IR format, run the following script to compile it into a `.blob` file, which can be deployed to the OAK-D device. +After converting the model to OpenVINO's IR format, run the following script to compile it into a `.blob` file, which can be deployed to the OAK-D device. ``` import blobconverter @@ -474,7 +474,7 @@ Planning groups in MoveIt 2 semantically describe different parts of the robot, ![moveit2\_assistant\_4](../../.gitbook/assets/robotic-arm-sorting-arduino-braccio/moveit2_assistant_4.png) -The Setup Assistant allows us to add predefined poses to the robot’s configuration, which can be useful for defining specific initial or ready poses. Later, the robot can be commanded to move to these poses using the MoveIt API. Click on the **Add Pose** and choose a name for the pose. +The Setup Assistant allows us to add predefined poses to the robot's configuration, which can be useful for defining specific initial or ready poses. Later, the robot can be commanded to move to these poses using the MoveIt API. Click on the **Add Pose** and choose a name for the pose. ![moveit2\_assistant\_5](../../.gitbook/assets/robotic-arm-sorting-arduino-braccio/moveit2_assistant_5.png)