Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org. I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the TF2 Mask R-CNN Inception ResNet V2 1024×1024 object detection model to test some sample images. The model was constructed using the Mask R-CNN Object detection model and trained on COCO 2017 dataset with training images scaled to 1024×1024.

Images Used: 1. Airport runway; 2. Tanzania Safari; 3. Streets with Cars; 4. Public Library

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

The HTML formatted report can be found here on GitHub.

Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org (https://www.tensorflow.org/hub/tutorials/object_detection). I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the TF2 Mask R-CNN Inception ResNet V2 1024×1024 object detection model to test some sample images. The model was constructed using the Mask R-CNN Object detection model and trained on COCO 2017 dataset with training images scaled to 1024×1024.

Original Script Location: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_object_detection.ipynb

Images Used: See project code below

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

The HTML formatted report can be found here on GitHub.

Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org (https://www.tensorflow.org/hub/tutorials/object_detection). I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the TF2 EfficientDet D4 1024×1024 object detection model to test some sample images. The model was constructed using the EfficientDet Object detection model (SSD with EfficientNet-b4 + BiFPN feature extractor, shared box predictor, and focal loss) and trained on COCO 2017 dataset with training images scaled to 1024×1024.

Original Script Location: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_object_detection.ipynb

Images Used: See project code below

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

The HTML formatted report can be found here on GitHub.

Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org (https://www.tensorflow.org/hub/tutorials/object_detection). I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the TF2 CenterNet HourGlass104 1024×1024 object detection model to test some sample images. The model was constructed using the CenterNet Object detection model with the Hourglass backbone and trained on COCO 2017 dataset with training images scaled to 1024×1024.

Original Script Location: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/tf2_object_detection.ipynb

Images Used: See project code below

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

The HTML formatted report can be found here on GitHub.

Template Credit: Adapted from an Object Detection tutorial on TensorFlow.org.

Additional Notes: I adapted this workflow from the TensorFlow Object Detection tutorial on TensorFlow.org (https://www.tensorflow.org/hub/tutorials/object_detection). I plan to build a script for building future projects using object detection models.

SUMMARY: This project aims to construct an object detection model using the TensorFlow-based neural network and document the end-to-end steps using a template.

This iteration will use the openimages_v4/ssd/mobilenet_v2 object detection model to test some sample images. The model was trained on Open Images V4 with ImageNet using pre-trained Inception Resnet V2 as an image feature extractor.

Original Script Location: https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/object_detection.ipynb

Images Used: See project code below

Dataset ML Model: Image Object Detection using TensorFlow Hub Models

Additional References: https://tfhub.dev/s?module-type=image-object-detection

The HTML formatted report can be found here on GitHub.