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* added SPPF module from yolov8 * added conv_block, bottleneck modules * cleaned modules * c2f example * spf changes * C2f * fixed and tested bottleneck * improved detect class * tested spf and conv * checked c2f * DFL structure * fixed dfl * added dist2bbox function * added dist2bbox function * added and tested make_anchors function for the head * keeping functions above * creating the detection head * fixing head * untested blocks a. scale_boxes b. clip_boxes c. xywh2xyxy d. box_iou * head works * structure fixx * added darknet (backbone) * yolov8 neck, and intialize bias function while detection * fixed spacing * yolov8 class, init bias, and fixed c2f * forward pass almost working * fixed net structure * init bias not needed, forward pass working * load weights boilerplate * load weights done? * all variants loading! * post process: clip_boxes, scale_boxes, xywh2xyxy, and box_iou(untested) * fix scale_boxes * box_iou fixed and tested * created the pre nms function * fix nms * fixed load weights, apparently the latest commit broke something, excluding num_batches_tracked * added letterbox and pre_tranform for pre_process function * fixed letterbox, pre_transform and added preprocess function * custom NMS done, integrated prepare_boxes and nms, improved box_iou * added postprocess function till parsing * added draw_bounding_boxes_and_save function * testing full flow * using fetch for class names * fixed make_anchors + all tinygrad now * added command line arguments, weight downloading * single image for now only * made draw boxes more efficient * made NMS functions efficient * made compute_transform better * v8 working now, inference is done * prints objects detected in console now * fixed image loading (pre processing) * batch post processing * created initial tests * fixes bounding box thickness AND added get_detected_classes_with_frequency function * cleaning for testing * two tests * added url option for image, removed need for specifiying arguments * tests complete, but lots on things are printed on screen by ultralytics * remove parse arguments * fixed weight location * fixed colours of classes, and black font when high brightness * minor changes * TODOs for later * removed use of torch, using .npz weights * fixed tests * one path for fetch * preprocess now in tinygrad, plus test fix for that * updated tests * fix tests * no class labels needed * Add files via upload * Update showcase.md * Update showcase.md * added safe tensors as weights, and tests fix for that * safe tensors test * using safe_load * using tinygrad functions now to load weights * update tests --------- Co-authored-by: r3sist-uniq <amanmatreja@gmail.com> Co-authored-by: r3sist <72573738+r3sist-uniq@users.noreply.github.com>
Welcome to the tinygrad documentation!
Here you will find documentation for tinygrad, as well as some examples and tutorials.
Getting Started
Read the quick start guide here.
Or if you want to jump right in to how tinygrad works, you can read the abstraction stack documentation.
Or if you want to see some examples, you can look at the examples in the examples directory.
Or if you just want to see some of the things tinygrad can do, check out the showcase.
API
This is currently a big work in progress.
Resources
Environment Variables
Adding New Accelerators
Community
Contributing
The documentation mainly follows the core contributing guidelines in the README.md.
Additionally, we always welcome documentation contributions, especially for features that are currently under documented.