rocauc

8 ms·

91.
by rocauc 6y ago
Appreciate it! Nice, I really respect research coming out of NIH. (Happen to know Travis Hoppe?) Coincidentally, our notebook demo for YOLOv5 is on the blood cell count and detection dataset: https://public.roboflow.ai/objec
92.
by rocauc 6y ago
Agreed! Crucially, we're tracking "out of the box" performance, e.g., if a developer grabbed X model and used it on a sample task, how could they expect it to perform? Further research and evaluation is recommended! For size,
93.
by rocauc 6y ago
Hey all - OP here. We're not affiliated with Ultralytics or the other researchers. We're a startup that enables developers to use computer vision without being machine learning experts, and we support a wide array of open source m
94.
by rocauc 6y ago
Great points, and hoping Glenn releases a paper to complement performance. We are also planning more rigorous benchmarking nonetheless. re: PyTorch being a confounding factor for speed - we recompiled YOLOv4 to PyTorch to achieve 50 FPS. Da
95.
by rocauc 6y ago
I remember following this as it came out (and learning windshield wipers should be called "swipey bois") Surprised and happy to hear you're seeing high labeling quality. We'll re-host with credit on https://pu
96.
by rocauc 6y ago
EfficientDet was open sourced March 18 [1], YOLOv4 came out April 23 [2], and now YOLOv5 is out only 48 days later. In our initial look, YOLOv5 is 180% faster, 88% smaller, similarly accurate, and easier to use (native to PyTorch rather tha
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YOLOv5: State-of-the-art object detection at 140 FPS(blog.roboflow.ai)
391 points by rocauc 6y ago|131 comments
98.
by rocauc 6y ago
YOLOv4 was published[1] on April 23 with COCO weights, but there haven't yet been resources on how to adapt its architecture to your own domain. This post walks through setting up Darknet and training on a custom dataset in Colab. FWIW
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Training YOLOv4 on a Custom Dataset(blog.roboflow.ai)
2 points by rocauc 6y ago|1 comments
100.
by rocauc 6y ago
this is a great breakdown on the WHY of SQL. giving clarity as to the what / why of SQL empowers those that don't yet know it how to make better asks for data in their organization.
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SQL for the Rest of Us(technically.dev)
16 points by rocauc 6y ago|2 comments
102.
by rocauc 6y ago
+1 to Pioneer's model
103.
by rocauc 6y ago
Yes, I'd recommend it. Pioneer gamifies your To-Do list, keeping you accountable and increasing your output. There's little downside to trying it out. I think there's been a fair number of Pioneer projects that go onto YC, to
104.
by rocauc 6y ago
The first self-driving tractors were used in research environments in 1996(!) [1] Automatic steering of farm vehicles using GPS. https://onlinelibrary.wiley.com/doi/abs/10.2134/1996.precisi... [2] First resul
105.
by rocauc 7y ago
As others have noted, this is data augmentation, and it's incredibly useful to increase variation in training data to help decrease overfitting. It's not a silver bullet. It won't capture the natural variations that happen in
106.
by rocauc 7y ago
The scary part isn't necessarily this dataset, but that unlabeled data causes a silent decrease in model performance -- which can be esp important for underrepresented classes.
107.
by rocauc 7y ago
Colab Notebook: https://bit.ly/rf-mn Associated Dataset: https://public.roboflow.ai/object-detection/bccd
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Tutorial: Using the TensorFlow Object Detection API on a Custom Dataset(blog.roboflow.ai)
2 points by rocauc 7y ago|1 comments
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Converting Annotations from Pascal VOC XML to Coco JSON(blog.roboflow.ai)
2 points by rocauc 7y ago|0 comments
110.
by rocauc 7y ago
Nice - I like how your project demonstrates a Bird’s Eye View angle works well. We’ll aim to support the view from a seated player on each side of the game.
111.
by rocauc 7y ago
So, as we think about making this into a production app, a feature you’d request is the ability for a user to add input as to why a given move is being suggested? At present, we’re simply outputting the recommended move from StockFish, whic
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by rocauc 7y ago
Nice. We’ll dive into your repo, too. How did you handle a queen occluding a smaller pawn behind it? Simply more training data?
113.
by rocauc 7y ago
We think streaming and creating game logs will be great features to add. We’ll likely share to the 147k /r/chess when we have an app others can demo. Good call.
114.
by rocauc 7y ago
Great minds! Love that you deployed to a Pi – I’ve thought about the same to complement or replace smartphones. Can you shed some insight into your ML process? One thing we did to simplify the vision problem is capture images from the same