Did-Somebody-Say-Corgi VS models

Have a look at the GitHub page for more information. You can use this Colab Notebook if you'd like synthesize your own corgi images or videos! You probably need some basic Python knowledge though.

Have a look at my [GitHub page](https://github.com/seawee1/Did-Somebody-Say-Corgi) for more information. You'll also find all the links there, i.e. one to the dataset (eventhough I'm not sure if anybody would actually need such a dataset :D) and the model checkpoints.

It took quite some time to aquire and preprocess the high-resolution corgi dataset, and even more time to train the model using Colab Pro (~18 days). Have a look at my [https://github.com/seawee1/Did-Somebody-Say-Corgi](GitHub page) for more information. You can also play around with it using this Colab notebook.

They're data-dependence graphs for a neural-network scheduling problem. Like this but way bigger to start with and then lowered to more detailed representations several times: https://netron.app/?url=https://github.com/onnx/models/raw/m... My home-grown layout engine can handle the 12k nodes for llama2 in its highest-level form in 20s or so, but its not the most featureful, and they only get bigger from there. So I always have an eye out for potential tools.

Uh, maybe they didn't feel the need to look. I already pointed you to the ONNX project. Here are some ONNX-based. These are just the ones being shared with the community. The limit of AMD's responsibility is writing the low-level libraries to support ONNX.

I am new to object detection models and I need help running my object detection Darknet YOLOv4-Tiny Model In Unity Barracuda. I trained my model and then i converted it to ONNX format with 2 methods. One method was using pytorch-YOLOv4 from github and the other by converting my model to tensorflow and then to onnx and shown here: "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb"

Then i tried to convert it again using another method that i found here "https://github.com/onnx/models/blob/main/vision/object_detection_segmentation/yolov4/dependencies/Conversion.ipynb" in order to convert it from darknet to tensorflow and then to onnx but i didn't have any luck.

Here we use the GPT-2 model distributed by the ONNX official. Download GPT-2-LM-HEAD from the link.

Download pre-trained models from the ONNX Model Zoo

Instructions to reproduce the problem: I am trying to convert a proprietary model at work but for now i'll use mobilenetv2-7.onnx to explain/reproduce the issue.

One approach could be run a pre-trained object detector (like one of these) on each frame and then a simple object tracker on top of it (like this).