* 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>
* resolved some slice test errors and added some more debugging logs
* use same device in cumsum
* increased float priority
* onnx debug ouput match input
* feat: promote Embedding to nn
* fix: fix failing test
* feat: add test with jit
* feat: rewrite embedding to no longer need stacked for loops
* clean+fix: don't know how that happened
* e2e testing
* min failure
* no affine on bn, still fails
* why did i think i could detach that?
* allow more kernels for bn
* some test issue i don't understand
* no zeroview start
* closer
* stride mask
* st tests pass, delete ZeroView
* byebye zv
* close to working
* not contiguous with mask
* subtract, don't add
* mask on view
* ugh, that shouldn't have been in there
* shape merge
* bugfixes
* fuzzer + 4 fuzzer failures
* fuzzer for symbolic
* more fuzzing and nothing
* that fuzzer doesn't hit either
* fixes padding...ugh
* no more offsets
* working
* rewrite load and store
* all checks
* fix idxs
* progress
* bugfix
* float4_axis
* works
* cleanups
* complex valids_okay
* make maximum split grad
* added test for maximum split grad when equal
* minor expr simplification
* (2-eq)/2 only once
* update test bc one more sum output child stays
* fix binop, other tests failure
* that was a bad idea
* better layernorm
* inference kernel count tests
* new style reshape pushing
* fixup replacement
* 199 kernels is okay. fix flops
* push reshape through unaryops only
* GRAPH=2 draws the phantom ops
* found resnet issue
* non working test
* mul is cheaper than div
* OPT inflation
* SHUFFLE_PAD_OPS in OPT=2
* runs one metal kernel
* conv2d works
* ops tests are passing
* const folding
* all ops work
* pre commit always passes
* torch works
* working still
* fix graph test
* tests passing
* image almost works
* image conv works
* most images
* fix custom
* fix assignment
* fix compile enet
* clean up comments
* fix realize return value
* include shapetracker in LB repr
* copy should make a copy
* reenable method cache
* fix lna
* dtypes in graph
* forward only for IMAGE=2
* simple realize
* getting close
* fixup new api, it's good except the kernel count
* back to 197 kernels
* tests should pass
* go to a real float
* no type_on_cpu
* fix the docs
* put shapetracker back in it's proper place
* Refactor contraction and add unit tests
* Fix typo; Fix TestConv.test_elu failure due to some ones in old_shape
* Add push permute test cases
* Fix mypy type annotation check error
* Add contraction unit test; Reshape to higher dimension is not contraction
