-
Notifications
You must be signed in to change notification settings - Fork 98
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Fix config option to split_by_inds
#1060
Conversation
Codecov Report
@@ Coverage Diff @@
## develop #1060 +/- ##
===========================================
+ Coverage 69.07% 69.12% +0.04%
===========================================
Files 127 127
Lines 21599 21601 +2
===========================================
+ Hits 14919 14931 +12
+ Misses 6680 6670 -10
📣 We’re building smart automated test selection to slash your CI/CD build times. Learn more |
@@ -20,6 +20,7 @@ | |||
import copy | |||
|
|||
import sleap | |||
from sleap import Labels |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Patch coverage is down because I changed all sleap.Labels
with Labels
. My feature is tested and uses Labels
so this shouldn't be a problem.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
See inline comments about using Labels.extract
instead of direct indexing. It might not be strictly necessary, but it would be beneficial while we're touching this part of the code.
If it doesn't work or if you see other issues with doing so, we can just go ahead and merge this as-is.
sleap/nn/training.py
Outdated
@@ -177,14 +178,13 @@ def from_labels( | |||
"Creating validation split from explicit indices " | |||
f"(n = {len(labels_config.validation_inds)})." | |||
) | |||
validation = training[labels_config.validation_inds] | |||
|
|||
validation = Labels(training[labels_config.validation_inds]) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Here and in subsequent places, do we maybe want to switch to using Labels.extract()
?
(In this case training.extract(labels_config.validation_inds, copy=False)
)
This retains other metadata which would be useful. We can skip using the copy=True
since that might slow things down for really large datasets, but at least using extract()
will avoid some weird issues with indexing videos and etc.
We may also want to switch to extract()
here in sleap.nn.data.training.split_labels_train_val()
for consistency:
sleap/sleap/nn/data/training.py
Lines 50 to 59 in 5093f69
# Create labels and keep original metadata. | |
labels_train = sleap.Labels(labels[idx_train]) | |
labels_train.videos = labels.videos | |
labels_train.tracks = labels.tracks | |
labels_train.provenance = labels.provenance | |
labels_val = sleap.Labels(labels[idx_val]) | |
labels_val.videos = labels.videos | |
labels_val.tracks = labels.tracks | |
labels_val.provenance = labels.provenance |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Some annotations for where the 3 functional changes are
from sleap.nn.data.utils import expand_to_rank, ensure_list | ||
from sleap.nn.data.utils import ensure_list | ||
import attr | ||
from typing import List, Text, Optional, Any, Union, Dict, Tuple, Sequence | ||
from typing import List, Text, Dict, Tuple, Sequence |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I removed unnecessary imports
@@ -3,20 +3,21 @@ | |||
import numpy as np | |||
import tensorflow as tf | |||
import sleap | |||
from sleap import Labels |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
I replaced sleap.Labels
with Labels
labels_train = sleap.Labels(labels[idx_train]) | ||
labels_train = labels.extract(idx_train, copy=False) | ||
labels_train.videos = labels.videos | ||
labels_train.tracks = labels.tracks | ||
labels_train.provenance = labels.provenance | ||
|
||
labels_val = sleap.Labels(labels[idx_val]) | ||
labels_val = labels.extract(idx_val, copy=False) | ||
labels_val.videos = labels.videos | ||
labels_val.tracks = labels.tracks | ||
labels_val.provenance = labels.provenance |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Functional change 1
split_labels.append(sleap.Labels([labels[int(ind)] for ind in sampled_indices])) | ||
split_labels.append( | ||
labels.extract([labels[int(ind)] for ind in sampled_indices]) | ||
) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Functional change 2
validation = training[labels_config.validation_inds] | ||
|
||
validation = training.extract(labels_config.validation_inds, copy=False) | ||
if labels_config.test_inds is not None and len(labels_config.test_inds) > 0: | ||
logger.info( | ||
"Creating test split from explicit indices " | ||
f"(n = {len(labels_config.test_inds)})." | ||
) | ||
test = training[labels_config.test_inds] | ||
test = training.extract(labels_config.test_inds, copy=False) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Functional change 3a
training = training[labels_config.training_inds] | ||
training = training.extract(labels_config.training_inds, copy=False) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Functional change 3b
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
lgtm
* GUI Training: Use hidden params from loaded config (#1053) * Add optional unragging arg to model export (#1054) * Fix config option to `split_by_inds` (#1060) * Convert training, validation, and test to Labels object * Add test for split_by_inds * Use Labels.extract instead of Labels(List[LabeledFrames]) * Tracking: robust assignment of the best score to an instance (#1062) * Set max instances for top down models (#1070) * Add optional unragging arg to model export * Add option to set max instances for multi-instance models * Fix test * Don't create instances during inference if no points were found (#1073) * Don't create instances during inference if no points were found * Add points check for all predictors * Fix single instance predictor logic and test * Add tests for all predictors Co-authored-by: roomrys <[email protected]> * Add one-line fix to VideoWriterSkyvideo (#1082) * Fix parser for sleap-export (#1085) * Refactor commands to load project as `AppCommand`s (#1098) * Add working Proof of Concept * Create command class for loading project * Split `LoadProjectFile` as a subclass of `LoadLabelsObject` * Reroute last existing reference * Remove debugging code * Flexibly resize input layer of `tf.keras.Model` upon loading trained model (#1084) * Add initial implementation (auto output stride problematic) * Add to load_predictor test (error when auto-compute output stride) * Use output stride from config instead of auto-computing * Fix output-stride/padding modulo error and do not resize on export * Fix resizing bug in multi-class predictors * Non-functional clean-up * Rename new input layer to original name * Add inference integration test * Minimize config surgery, generalize layer iteration Co-authored-by: Talmo Pereira <[email protected]> * Add Option to Make Trail Shade Darker/Lighter (#1103) * Make trails 60% darker than track color * Add menu option for shade of trails * Remove unexpected indent (fat-fingered) * Create signal that updates plot instead of removing and replotting items (#1134) * Create signal that updates plot instead of redrawing * Remove debug code * Non-functional self-review changes * Fix symmetric skeletons (via table input) (#1136) Ensure variable initialized before calling it * Nix export of tracking results (#1068) * [io] export tracking results to NIX file * [io] nix added to export filter only if available * [nixio] refactor, add scores link data as mtag * [nixio] speeding up export by chunked writing * [nixio] rename point score to node score * [nixio] fix missing dimension descriptor for node scores * [export analysis] support multiple formats also for bulk export * [nixio] export centroid, some documentation * [nixio] fix double dot before filename suffix * [nixio] fix bug when not all nodes were found * [nixio] housekeeping * [nix] add nix analyis output format to convert * [nix] tiny fix, catch file write error and properly close file * [inference] main takes optional args. Can be imported to run inference form scripts * [convert] simplify if else structure and outfile handling for analysis export * [nix] use pathlib instead of os * [nix] catch if there are instances with a None frame_idx ... not sure why this occurred. The nix adaptor cannot save instances that are not related to a frame. * [nix] move checks to top of write function * [nix] use absolute imports * [nix] use black to reformat * [commands] revert qtpy import and apply code style * [convert] use absolute imports, apply code style * [commands]fix imports * [inference/nix]fix linter complaint, adjust nix types for scores * [nix] add test case for nix export format * [nix] extended testing, some modifications of adaptor * [skeleton] add __eq__ to Skeleton ... make Node.name and Node.weight instance variables instead of class variables * [nix] add nixio to requirements, remove unused nix_available, ... allow for non-unique entries in node, track and skeleton. Extend node map to store the skeleton it is part of * [nix] make the linter happy * [Node] force definition of a name Co-authored-by: Liezl Maree <[email protected]> * [nix] use getattr for getting grayscale information Co-authored-by: Liezl Maree <[email protected]> * [nix] fixes according to review * [convert] break out of loop upon finding the video Co-authored-by: Liezl Maree <[email protected]> * [commands.py] use pathilb instead of splitting filename Co-authored-by: Liezl Maree <[email protected]> * [dev requirements] remove linebreak at last line * [skeleton] revert attribute creation back to original * [nix] break lines in class documentation * Ensure all file references are closed * Make the linter happy * Add tests for ExportAnalysis and (docs for) sleap-convert Co-authored-by: Liezl Maree <[email protected]> * Fix body vs symmetry subgraph filtering (#1142) Co-authored-by: Liezl Maree <[email protected]> * Handle changing backbones in training editor GUI (#1140) Co-authored-by: Liezl Maree <[email protected]> * Added scaling functionality for both the instances and bounding box. (#1133) * Create VisibleBoundingBox class. * Added instance scaling functionality in addition to bounding box scaling functionality. * Update sleap/gui/widgets/video.py Co-authored-by: Talmo Pereira <[email protected]> * Update sleap/gui/widgets/video.py Co-authored-by: Talmo Pereira <[email protected]> * Update sleap/gui/widgets/video.py Co-authored-by: Talmo Pereira <[email protected]> * Update sleap/gui/widgets/video.py Co-authored-by: Talmo Pereira <[email protected]> * Update sleap/gui/widgets/video.py Co-authored-by: Talmo Pereira <[email protected]> * Added new testing for scaling operation and simplified VisibleBoundingBox class code. * Added type hinting to the scaling padding and removed erroneous bounding rect initialization. Co-authored-by: Talmo Pereira <[email protected]> Co-authored-by: Liezl Maree <[email protected]> * Add better error message for top down (#1121) * Add better error message for top down * Add test for error message * Raise different error, fix test * Hotfix for video save #1098 (#1148) * Add a hotfix for #1098 * WIP: Add test for detecting changes on load * Finialize change on load test * Remove unused imports * Skip test if on windows since files are being used in parallel * Add central padding to SizeMatcher (#1129) * add center padding to size matcher * add test for center padding * add ensure_float option to inference layer * reformat resizing and test_resizing * Remove redundant operation * Replace existing constants with fixtures --------- Co-authored-by: Liezl Maree <[email protected]> * Added MoveNet as an external model reference (#1141) * add center padding to size matcher * add test for center padding * add ensure_float option to inference layer * reformat resizing and test_resizing * add MoveNet as an external model inference * add the movenet to the from_model_paths * add tests * add comments to movenet predictor * add tensorflow_hub to the requirements.txt * modified default video path * resolved most of the comments except expanding the predictor * expanded Predictor.from_model_paths function to include any pre-trained models. * add test_load_model * added from_trained_models in class Predictor and modified test_load_model for it. * modified test_load_model to be more generalized. * moved pretrained model from Predictor.from_trained_model to Predictor.from_model_paths and added a test for it. * Fix Predictor.from_model_paths and tests * Rename load_movenet_model to make_model_movenet * minor clean-up * Remove redundant operation * Replace existing constants with fixtures * Handle loading movenet models via load_model API * Clean-up doc strings --------- Co-authored-by: Liezl Maree <[email protected]> * Resumable Training (#1130) * add resume training functionality * add testing function for resume training functionality * linting black * Resumable Training 2 - CLI Options (#1131) * add cli options for resumable training * add test for cli resume training * black linting for cli resumable training * simplify resumable checkpoint CLI fn to a single CLI arg (#1132) * simplify resumable checkpoint CLI fn to a single CLI arg * Adam/resumable training 3 (#1150) * correct path of labels_path for test_training * add resume training to gui * add train from scratch message * Add finishing touches to resumable training PR (#1150) (#1168) * Refactor/update 'use trained' and 'resume training' checkbox logic * Simplify checkbox logic and reset model field when resume training * Reset checkboxes upon changing config selection * Handle case for updating TrainingEditor when sender is not a checkbox * Add complete state space GUI test for checkboxes * Finish combobox test * Test that form is reset * Remove straggling TODO --------- Co-authored-by: roomrys <[email protected]> Co-authored-by: jimzers <[email protected]> --------- Co-authored-by: jimzers <[email protected]> Co-authored-by: Liezl Maree <[email protected]> * Return trainer from sleap-train and check that trainer configured correctly * Add CLI documentation for website --------- Co-authored-by: jimzers <[email protected]> Co-authored-by: Liezl Maree <[email protected]> * Small (final?) revisions and fix test * Revert changes to fixture --------- Co-authored-by: jimzers <[email protected]> Co-authored-by: Liezl Maree <[email protected]> * GenericTableModel/View improvements (#1163) * [dataviews] GenericTableModel/View improvements ... * GenericTableView got a new argument specifying whether the ellipsis for long cell content should be right (old behavior, default) or left useful for long content such as the filenames in the video table. * GenericTableView uses all the space that available to the table. * The model's data function returns the full cell content to be shown as tool tip text. * [gui/app] set the ellipsis to be on the left for long table contents --------- Co-authored-by: Liezl Maree <[email protected]> * Add Skeleton Templates (#1122) * Update docs: change 'M1' to 'Apple Silicon' (#1188) * Bump to 1.3.0a0 (#1189) --------- Co-authored-by: sheridana <[email protected]> Co-authored-by: getzze <[email protected]> Co-authored-by: Talmo Pereira <[email protected]> Co-authored-by: Jan Grewe <[email protected]> Co-authored-by: Sean Afshar <[email protected]> Co-authored-by: Jiaying Hsu <[email protected]> Co-authored-by: Adam Lee <[email protected]> Co-authored-by: jimzers <[email protected]> Co-authored-by: Jan Grewe <[email protected]> Co-authored-by: Aaditya Prasad <[email protected]>
Description
Fix config option to
split_by_inds
. Previously triaining would fail when"split_by_inds": true
due to improper handling of training, test, and validation indices. This PR converts the test, train, and validation sets to the format they are expected to be inLabels
instead ofList[LabeledFrame]
.Types of changes
Does this address any currently open issues?
split_by_inds
is broken #1059Outside contributors checklist
Thank you for contributing to SLEAP!
❤️