Dev/feature yolo

pyproject.toml

@@ -60,6 +60,7 @@ pillow = "^9.2.0"
 pytest = "^7.2.0"
 unittest2 = "^1.1.0"
 torch = "^1.13.1"
+opencv-python-headless = "^4.8.1.78"
 
 [tool.poetry.dev-dependencies]
 bandit = "1.7.4"
@@ -178,3 +179,9 @@ pycodestyle = ["-F401"]                     # Disable a check
 flake8-bandit = ["-S101"]                   # Ignore asserts for tests
 pyflakes = ["-*"]                           # Disable a plugin
 
+[tool.flakeheaven.exceptions."src/lava/lib/dl/slayer/object_detection/models/*"]
+pycodestyle = ["-E501", "-E241", "-E221"]   # Disable a check
+
+[tool.flakeheaven.exceptions."tutorials/lava/lib/dl/slayer/tiny_yolo_sdnn/train_sdnn.py"]
+pycodestyle = ["-E501"]                     # Disable a check
+

src/lava/lib/dl/slayer/README.md

@@ -125,6 +125,9 @@ class Network(torch.nn.Module):
 <img src="https://user-images.githubusercontent.com/29907126/135402787-ca849ef2-697d-4c5c-9f05-9b6fe3c3b072.png" alt="Drawing" style="height: 400px;"/>
 </p>
 
+### Object detection mdoule (`slayer.obd`)
+`slayer.obd` includes object detection specific modules, utilities and some pre-designed object detection networks. These can be used to design and train your custon SNN based object detection networks using SLAYER. More details can be found [here](https://github.com/lava-nc/lava-dl/blob/main/src/lava/lib/dl/slayer/object_detection/README.md).
+
 ### Fundamental Practices
 
 * Tensors are always assumed to be in the order `NCHWT` or `NCT` where `N`:Batch, `C`:Channel, `H`: Height(y), `W`: Width(x) and `T`: Time. 

src/lava/lib/dl/slayer/__init__.py

@@ -12,6 +12,7 @@
 from . import io
 from . import auto
 from . import utils
+from . import object_detection as obd
 
 __all__ = [
     'neuron',
@@ -24,5 +25,6 @@
     'loss',
     'io',
     'auto',
-    'utils'
+    'utils',
+    'obd'
 ]

src/lava/lib/dl/slayer/loss.py

@@ -286,3 +286,44 @@ def forward(self, input, label):
                 label.flatten(),
                 reduction=self.reduction
             )
+
+
+class SparsityEnforcer:
+    """Event sparsity enforcement module. Penalizes event rate higher than
+    a specific value.
+
+    Parameters
+    ----------
+    max_rate : float, optional
+        Rate above which the events are penalized, by default 0.01.
+    lam : float, optional
+        Ratio of event rate loss scaling, by default 1.0.
+    """
+    def __init__(self, max_rate: float = 0.01, lam: float = 1.0) -> None:
+        self.max_rate = max_rate
+        self.lam = lam
+        self.loss_list = []
+
+    def clear(self) -> None:
+        """Clear all gathered sparsity loss.
+        """
+        self.loss_list = []
+
+    @property
+    def loss(self) -> torch.tensor:
+        """Accumulate sparsity loss.
+        """
+        return self.lam * sum(self.loss_list)
+
+    def append(self, x: torch.tensor) -> None:
+        """Appends loss tickets given the state of input tensors.
+
+        Parameters
+        ----------
+        x : torch.tensor
+            Input tensor.
+        """
+        mean_event_rate = torch.mean(torch.abs(x))
+        self.loss_list.append(F.mse_loss(F.relu(mean_event_rate
+                                                - self.max_rate),
+                                         torch.zeros_like(mean_event_rate)))

src/lava/lib/dl/slayer/object_detection/README.md

@@ -0,0 +1,8 @@
+## Lava-DL SLAYER Object detection module
+
+Lava-dl now includes object detection module which can be accessed as `from lava.lib.dl.slayer import obd` or as `slayer.obd`. The object detection module includes
+
+* Base YOLO class `obd.yolo_base` which can be used to design and train YOLO SNNs.
+* Pre-formulated model descriptions and pre-trained models `obd.models.{tiny_yolov3_str, yolo_kp, *}`.
+* Bounding box metrics and utilities `obd.bbox.{metrics, utils}` to facilitate video object detection training with spiking neurons.
+* Dataset modules and utilities `obd.dataset.{BDD, utils}`. Currently there is support for [Berkley Deep Drive (BDD100K)](https://bdd-data.berkeley.edu/) dataset. More dataset support will be added in the future.

src/lava/lib/dl/slayer/object_detection/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier:  BSD-3-Clause
+
+from . import boundingbox as bbox
+from . import boundingbox, dataset, models
+from .yolo_base import YOLOtarget, YOLOLoss, YOLOBase
+
+
+__all__ = [
+    'bbox', 'boundingbox', 'dataset',
+    'models', 'YOLOtarget',
+    'YOLOLoss', 'YOLOBase'
+]

src/lava/lib/dl/slayer/object_detection/boundingbox/__init__.py

@@ -0,0 +1,7 @@
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier:  BSD-3-Clause
+
+from . import metrics
+from . import utils
+
+__all__ = ['metrics', 'utils']