roboflow-100-benchmark
make-sense
| roboflow-100-benchmark | make-sense | |
|---|---|---|
| 1 | 7 | |
| 103 | 2,969 | |
| - | - | |
| 10.0 | 2.4 | |
| over 1 year ago | about 2 months ago | |
| Jupyter Notebook | TypeScript | |
| MIT License | GNU General Public License v3.0 only |
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roboflow-100-benchmark
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Roboflow 100: A New Object Detection Benchmark
Thanks for sharing @jonbaer! Iām one of the co-founders of Roboflow. Some additional resources and context:
* Blog Post: https://blog.roboflow.com/roboflow-100/
* Paper: https://arxiv.org/abs/2211.13523
* Github: https://github.com/roboflow-ai/roboflow-100-benchmark
At Roboflow, we've seen users fine-tune hundreds of thousands of computer vision models on custom datasets.
We observed that there's a huge disconnect between the types of tasks people are actually trying to perform in the wild and the types of datasets researchers are benchmarking their models on.
Datasets like MS COCO (with hundreds of thousands of images of common objects) are often used in research to compare models' performance, but then those models are used to find galaxies, look at microscope images, or detect manufacturing defects in the wild (often trained on small datasets containing only a few hundred examples). This leads to big discrepancies in models' stated and real-world performance.
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?
roboflow-100-benchmark - Code for replicating Roboflow 100 benchmark results and programmatically downloading benchmark datasets
label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format
sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots
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]
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
AID - One-Stop System for Machine Learning.
yolov5 - YOLOv5 š in PyTorch > ONNX > CoreML > TFLite
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.
SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data
pytorch-pose-hg-3d - PyTorch implementation for 3D human pose estimation