agosztolai
commented
3 months ago Open agosztolai opened 3 months ago
agosztolai
commented
3 months ago agosztolai
commented
3 months ago Ok, I think I have figured this out. The issue seems to be that I have defined a skeleton with two connected components. I noticed this because I tried to use the same pipeline as in the tutorial. The tutorial uses a multi-animal model in which the "Run" button is disabled when there are multiple connected components. However, the single-animal model trains well with skeletons having multiple connected components. Except that at inference time, no predicted instances are returned.
Could this be the issue that the model only accepts a single connected component? If yes, it would be nice to include a checkpoint for this in the code.
Lateef-Saheed
commented
3 months ago Hello! I am having a similar issue as you. Just curious if in your training settings, you have the "rotate" setting in the Augmentation section of the Single Instance Model configuration tab checked?
agosztolai
commented
3 months ago Yes, for me it works with ‘rotate’ on. Perhaps try rotate = off. If that works, maybe report the bug?
On 25 Jun 2024, at 20:14, Lateef-Saheed @.***> wrote:
Hello! I am having a similar issue as you. Just curious if in your training settings, you have the "rotate" setting in the Augmentation section of the Single Instance Model configuration tab checked?
— Reply to this email directly, view it on GitHub https://github.com/talmolab/sleap/issues/1821#issuecomment-2189659113, or unsubscribe https://github.com/notifications/unsubscribe-auth/AK6WK5D3VZLGACSWFN2PP2LZJGXP7AVCNFSM6AAAAABJVZQP2OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCOBZGY2TSMJRGM. You are receiving this because you authored the thread.
Lateef-Saheed
commented
3 months ago Sounds good, I tried turning off rotation and that got me inferences, albeit ones that weren't accurate. Thanks for the confirmation!
talmo
commented
2 months ago Hi folks,
Apologies for the delay! We're a bit behind on support responses at the moment.
Neither rotation nor the skeleton edge configuration should make any difference to the single animal model.
If you're not getting predictions, the most likely cause is that the model is underperforming. The easiest thing to try is to just add more labels, but it might be that further model parameter tuning would help.
Turning off rotation will cause the model to seriously overfit, which means it'll work on images very similar to those in your training data, but fail to generalize to new ones.
It sounds like @agosztolai has a working solution, but @Lateef-Saheed if you don't mind creating a new Discussion with some information about your project, we'd be happy to help!
Lateef-Saheed
commented
2 months ago Noted! We ended up labeling more frames and using the "Latest" model instead of "Best" and it ended up giving us predictions. I am curious about your comment about rotation. What exactly does the rotation augmentation feature mean and how would not selecting it result in failing to generalize to new videos? Thanks for the help!
On Fri, Jul 19, 2024 at 7:02 PM Talmo Pereira @.***> wrote:
Hi folks,
Apologies for the delay! We're a bit behind on support responses at the moment.
Neither rotation nor the skeleton edge configuration should make any difference to the single animal model.
If you're not getting predictions, the most likely cause is that the model is underperforming. The easiest thing to try is to just add more labels, but it might be that further model parameter tuning would help.
Turning off rotation will cause the model to seriously overfit, which means it'll work on images very similar to those in your training data, but fail to generalize to new ones.
It sounds like @agosztolai https://github.com/agosztolai has a working solution, but @Lateef-Saheed https://github.com/Lateef-Saheed if you don't mind creating a new Discussion https://github.com/talmolab/sleap/discussions with some information about your project, we'd be happy to help!
— Reply to this email directly, view it on GitHub https://github.com/talmolab/sleap/issues/1821#issuecomment-2240781386, or unsubscribe https://github.com/notifications/unsubscribe-auth/BG7CTUA3QCZDTGFHPUO23JTZNGSKFAVCNFSM6AAAAABJVZQP2OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDENBQG44DCMZYGY . You are receiving this because you were mentioned.Message ID: @.***>
Bug description
After training, the inference step outputs no labels.
Expected behaviour
I expect labels (yellow markers) to emerge in the GUI after inference.
Actual behaviour
Nothing happens.
Your personal set up
Environment packages
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(sleap) adamgosztolai@Adams-MacBook-Pro-2 data % sleap-label Saving config: /Users/adamgosztolai/.sleap/1.3.3/preferences.yaml Restoring GUI state... Software versions: SLEAP: 1.3.3 TensorFlow: 2.9.2 Numpy: 1.22.4 Python: 3.9.15 OS: macOS-14.5-arm64-arm-64bit Happy SLEAPing! :) qt.qpa.fonts: Populating font family aliases took 155 ms. Replace uses of missing font family ".AppleSystemUIFont" with one that exists to avoid this cost. Resetting monitor window. Polling: /Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/models/calibration240621_144245.single_instance.n=1/viz/validation.*.png Start training single_instance... ['sleap-train', '/var/folders/3n/71gnzd013y5f29s9t0tyyrwh0000gn/T/tmpnecxtno4/240621_144245_training_job.json', '/Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/labels.v001.slp', '--zmq', '--save_viz'] INFO:sleap.nn.training:Versions: SLEAP: 1.3.3 TensorFlow: 2.9.2 Numpy: 1.22.4 Python: 3.9.15 OS: macOS-14.5-arm64-arm-64bit INFO:sleap.nn.training:Training labels file: /Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/labels.v001.slp INFO:sleap.nn.training:Training profile: /var/folders/3n/71gnzd013y5f29s9t0tyyrwh0000gn/T/tmpnecxtno4/240621_144245_training_job.json INFO:sleap.nn.training: INFO:sleap.nn.training:Arguments: INFO:sleap.nn.training:{ "training_job_path": "/var/folders/3n/71gnzd013y5f29s9t0tyyrwh0000gn/T/tmpnecxtno4/240621_144245_training_job.json", "labels_path": "/Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/labels.v001.slp", "video_paths": [ "" ], "val_labels": null, "test_labels": null, "base_checkpoint": null, "tensorboard": false, "save_viz": true, "zmq": true, "run_name": "", "prefix": "", "suffix": "", "cpu": false, "first_gpu": false, "last_gpu": false, "gpu": "auto" } INFO:sleap.nn.training: INFO:sleap.nn.training:Training job: INFO:sleap.nn.training:{ "data": { "labels": { "training_labels": null, "validation_labels": null, "validation_fraction": 0.1, "test_labels": null, "split_by_inds": false, "training_inds": null, "validation_inds": null, "test_inds": null, "search_path_hints": [], "skeletons": [] }, "preprocessing": { "ensure_rgb": false, "ensure_grayscale": false, "imagenet_mode": null, "input_scaling": 1.0, "pad_to_stride": null, "resize_and_pad_to_target": true, "target_height": null, "target_width": null }, "instance_cropping": { "center_on_part": null, "crop_size": null, "crop_size_detection_padding": 16 } }, "model": { "backbone": { "leap": null, "unet": { "stem_stride": null, "max_stride": 16, "output_stride": 2, "filters": 16, "filters_rate": 2.0, "middle_block": true, "up_interpolate": true, "stacks": 1 }, "hourglass": null, "resnet": null, "pretrained_encoder": null }, "heads": { "single_instance": { "part_names": null, "sigma": 2.5, "output_stride": 2, "loss_weight": 1.0, "offset_refinement": false }, "centroid": null, "centered_instance": null, "multi_instance": null, "multi_class_bottomup": null, "multi_class_topdown": null }, "base_checkpoint": null }, "optimization": { "preload_data": true, "augmentation_config": { "rotate": true, "rotation_min_angle": -15.0, "rotation_max_angle": 15.0, "translate": false, "translate_min": -5, "translate_max": 5, "scale": false, "scale_min": 0.9, "scale_max": 1.1, "uniform_noise": false, "uniform_noise_min_val": 0.0, "uniform_noise_max_val": 10.0, "gaussian_noise": false, "gaussian_noise_mean": 5.0, "gaussian_noise_stddev": 1.0, "contrast": false, "contrast_min_gamma": 0.5, "contrast_max_gamma": 2.0, "brightness": false, "brightness_min_val": 0.0, "brightness_max_val": 10.0, "random_crop": false, "random_crop_height": 256, "random_crop_width": 256, "random_flip": true, "flip_horizontal": false }, "online_shuffling": true, "shuffle_buffer_size": 128, "prefetch": true, "batch_size": 1, "batches_per_epoch": null, "min_batches_per_epoch": 200, "val_batches_per_epoch": null, "min_val_batches_per_epoch": 10, "epochs": 2, "optimizer": "adam", "initial_learning_rate": 0.0001, "learning_rate_schedule": { "reduce_on_plateau": true, "reduction_factor": 0.5, "plateau_min_delta": 1e-06, "plateau_patience": 5, "plateau_cooldown": 3, "min_learning_rate": 1e-08 }, "hard_keypoint_mining": { "online_mining": false, "hard_to_easy_ratio": 2.0, "min_hard_keypoints": 2, "max_hard_keypoints": null, "loss_scale": 5.0 }, "early_stopping": { "stop_training_on_plateau": true, "plateau_min_delta": 1e-08, "plateau_patience": 10 } }, "outputs": { "save_outputs": true, "run_name": "240621_144245.single_instance.n=1", "run_name_prefix": "calibration", "run_name_suffix": "", "runs_folder": "/Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/models", "tags": [ "" ], "save_visualizations": true, "delete_viz_images": true, "zip_outputs": false, "log_to_csv": true, "checkpointing": { "initial_model": false, "best_model": true, "every_epoch": false, "latest_model": false, "final_model": false }, "tensorboard": { "write_logs": false, "loss_frequency": "epoch", "architecture_graph": false, "profile_graph": false, "visualizations": true }, "zmq": { "subscribe_to_controller": true, "controller_address": "tcp://127.0.0.1:9000", "controller_polling_timeout": 10, "publish_updates": true, "publish_address": "tcp://127.0.0.1:9001" } }, "name": "", "description": "", "sleap_version": "1.3.3", "filename": "/var/folders/3n/71gnzd013y5f29s9t0tyyrwh0000gn/T/tmpnecxtno4/240621_144245_training_job.json" } INFO:sleap.nn.training: INFO:sleap.nn.training:Failed to query GPU memory from nvidia-smi. Defaulting to first GPU. INFO:sleap.nn.training:Using GPU 0 for acceleration. INFO:sleap.nn.training:Disabled GPU memory pre-allocation. INFO:sleap.nn.training:System: GPUs: 1/1 available Device: /physical_device:GPU:0 Available: True Initalized: False Memory growth: True INFO:sleap.nn.training: INFO:sleap.nn.training:Initializing trainer... INFO:sleap.nn.training:Loading training labels from: /Users/adamgosztolai/Documents/GitHub/large_kinematic_model/preprocessing/sleap/labels.v001.slp INFO:sleap.nn.training:Creating training and validation splits from validation fraction: 0.1 INFO:sleap.nn.training: Splits: Training = 1 / Validation = 1. INFO:sleap.nn.training:Setting up for training... INFO:sleap.nn.training:Setting up pipeline builders... INFO:sleap.nn.training:Setting up model... INFO:sleap.nn.training:Building test pipeline... Metal device set to: Apple M3 Pro systemMemory: 36.00 GB maxCacheSize: 13.50 GB 2024-06-21 14:42:49.053848: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support. 2024-06-21 14:42:49.053983: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: