SynthDet
make-sense
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| SynthDet | make-sense | |
|---|---|---|
| 3 | 7 | |
| 350 | 2,965 | |
| 0.9% | - | |
| 2.9 | 2.4 | |
| 10 months ago | about 2 months ago | |
| C# | TypeScript | |
| Apache License 2.0 | GNU General Public License v3.0 only |
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SynthDet
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Looking for 3D food packaging assets
Didn't try but Unity did a object recognition project with store products: https://github.com/Unity-Technologies/SynthDet. You can find the models and texture in the "Assets/Foreground Objects" folder. And you may need to check the license depending on your usage.
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How to generate images and labels using unity (or other game engine) to train YOLO5 object detection model? (Synthetic Data generation using unity for neural network learning). Are there any existing solutions or guides?
This is probably what you're looking for . https://github.com/Unity-Technologies/SynthDet
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Imported materials for objects can't edit.
So I'm working on Unity with this Project (SynthDet) https://github.com/Unity-Technologies/SynthDet and I'm working on imported objects (obj. ), trying to edit materials of those objects, but I can't. The materials are gredy out. Don't know what to do. Do you guys have any ideas what to do, to allow to edit imported materials?
make-sense
- Need help identifying a good open source data annotation tool
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Free instance segmentation annotation tool
Hi šš»! Iām creator of https://makesense.ai. It supports Instance Segmentation. Take a look at the repo: https://github.com/SkalskiP/make-sense
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Data Labelling Software
I created tool called MakeSense: https://github.com/SkalskiP/make-sense it is completely free and open sourced on GH
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Roboflow 100: A New Object Detection Benchmark
Haven't heard of those two, but would be really awesome to see an integration. We have an open API[1] for just this reason: we really want to make it easy to use (and source) your data across all the different tools out there. We've recently launched integrations with other labeling[2] and AutoML[3] tools (and have integrations with the big-cloud AutoML tools as well[4]). We're hoping to have a bunch more integrations with other MLOps tools & platforms in 2023.
Re synthetic data specifically, we've written a couple of how-to guides for creating data from context augmentation[5], Unity Perception[6], and Stable Diffusion[7] & are talking to some others as well; it seems like a natural integration point (and someplace where we don't need to reinvent the wheel).
[1] https://docs.roboflow.com/rest-api
[2] https://github.com/SkalskiP/make-sense/pull/298
[3] https://github.com/ultralytics/yolov5/discussions/10425
[4] https://docs.roboflow.com/train/pro-third-party-training-int...
[5] https://blog.roboflow.com/how-to-create-a-synthetic-dataset-...
[6] https://blog.roboflow.com/unity-perception-synthetic-dataset...
[7] https://blog.roboflow.com/synthetic-data-with-stable-diffusi...
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[Project] Football Players Tracking with YOLOv5 + ByteTRACK
Two things that carried me the most are my blog https://medium.com/@skalskip - which gave me my first job in computer vision, and my open-source GitHub project: https://github.com/SkalskiP/make-sense - which gave me all my jobs since I created it.
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Hi everyone! I'm Piotr and for several years I have been developing a small open-source project for labeling photos - makesense.ai. I added a new feature this weekend. You can use YOLOv5 models to automatically annotate photos.
Link to GitHub project: https://github.com/SkalskiP/make-sense
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Tool for human pose estimation keypoint annotation
I have also looked into make-sense and currently the docker and the npm refuse to work. I have already opened a ticket describing the issue .
What are some alternatives?
AI-basketball-analysis - :basketball::robot::basketball: AI web app and API to analyze basketball shots and shooting pose.
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
Deep-Learning-Push-Up-Counter - Deep Learning approach to count the number of repetitions in a video of push ups or pull ups.
cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0
AID - One-Stop System for Machine Learning.
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.
Universal Data Tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.
Mask-RCNN-Implementation - Mask RCNN Implementation on Custom Data(Labelme)
pytorch-pose-hg-3d - PyTorch implementation for 3D human pose estimation