lemon-dataset
albumentations
| lemon-dataset | albumentations | |
|---|---|---|
| 1 | 28 | |
| 98 | 13,425 | |
| - | 0.9% | |
| 0.0 | 8.9 | |
| almost 4 years ago | 7 days ago | |
| Python | ||
| - | MIT License |
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lemon-dataset
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computer vision project
I give you one dataset https://github.com/softwaremill/lemon-dataset . It can be useful to spot lemons problem and can be a good proxy for the task discussed above. Then if you are looking on fine grained product classification there are open dataset also for this task.
albumentations
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Augment specific classes?
You can use albumentations if you are comfortable with using open source libraries https://github.com/albumentations-team/albumentations
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Ask HN: What side projects landed you a job?
One of the members of the core team of our open-source library https://albumentations.ai/
It was not the only reason he was hired; it was a solid addition to his already good performance at the interviews.
Or at least that is what the hiring manager later said.
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The Lack of Compensation in Open Source Software Is Unsustainable
I am one of the creators and maintainers of https://albumentations.ai/.
- 12800+ stars
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Burn Deep Learning Framework Release 0.7.0: Revamped (de)serialization, optimizer & module overhaul, initial ONNX support and tons of new features.
Is something planned to support data augmentations? Something like https://albumentations.ai/
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How to label augmented images for training YOLO algorithm?
Here you go: https://albumentations.ai/
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Unstable Diffusion bounces back with $19,000 raised in one day, by using Stripe
I think they should use some data augmentation techniques like I am using for Infinity AI if you wanna see more here. Note that most of these do not work for image generation.
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Tokyo Drift : detecting drift in images with NannyML and Whylogs
Our second approach was a more automated one. Here the idea was to try out an image augmentation library, Albumentations, and use it for adversarial attacks. This time, instead of one-shot images, we applied the transformations at random time ranges. We chose for these transformations also to be more subtle than then one-shot images, such as vertical flips, grayscaling, downscaling, …
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[D] Improve machine learning with same number of images
Check out albumentations. If your use case is segmentation, check out the offline augmentation of this project
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What are the best programs/scripts for image augmentation of YOLO5 training dataset. Something like roboflow but free)
I think this is the most popular open source project: https://github.com/albumentations-team/albumentations
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To get dataset for face image restoration.
You can also curate your own dataset by using open source images (https://universe.roboflow.com/search?q=faces%20images%3E1000) and open source augmentations (https://github.com/albumentations-team/albumentations). Or you can do use the augmentation UI (https://docs.roboflow.com/image-transformations/image-augmentation) to apply noise, blurring, shear, crop, etc.
What are some alternatives?
Hello-Kaggle - For someone who is new at Kaggle
imgaug - Image augmentation for machine learning experiments.
jetson-inference - Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
YOLO-Mosaic - Perform mosaic image augmentation on data for training a YOLO model
datasets-for-good - List of datasets to apply stats/machine learning/technology to the world of social good.
labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.
awesome-project-ideas - Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
ttach - Image Test Time Augmentation with PyTorch!
image-statistics-matching - Methods for alignment of global image statistics aimed at unsupervised Domain Adaptation and Data Augmentation