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Initial support for Hailo-8L (#12431)

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* Initial support for Hailo-8L

Added file for Hailo-8L detector including dockerfile, h8l.mk, h8l.hcl, hailo8l.py, ci.yml and ssd_mobilenat_v1.hef as the inference network.

Added files to help with the installation of Hailo-8L dependences like generate_wheel_conf.py, requirements-wheel-h8l.txt and modified setup.py to try and work with any hardware.

Updated docs to reflect Initial Hailo-8L support including oject_detectors.md,  hardware.md and installation.md.

* Update .github/workflows/ci.yml

typo h8l not arm64

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

* Update docs/docs/configuration/object_detectors.md

Clarity for the end user and correct uses of words

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

* Update docs/docs/frigate/installation.md

typo

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>

* update Installation.md to clarify Hailo-8L installation process.

* Update docs/docs/frigate/hardware.md

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>

* Update hardware.md add Inference time.

* Oops no new line at the end of the file.

* Update docs/docs/frigate/hardware.md typo

Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>

* Update dockerfile to download the ssd_modilenet_v1 model instead of having it in the repo.

* Updated dockerfile so it dose not download the model file.

add function to download it at runtime.

update model path.

* fix formatting according to ruff and removed unnecessary functions.

---------

Co-authored-by: Nicolas Mowen <nickmowen213@gmail.com>
Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com>
This commit is contained in:
spanner3003
2024-07-14 18:17:02 +01:00
committed by Nicolas Mowen
parent e7fabce4e0
commit 4a35573210
12 changed files with 689 additions and 1 deletions
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docs/docs/configuration/object_detectors.md
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@@ -5,7 +5,7 @@ title: Object Detectors
# Officially Supported Detectors
Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `openvino`, `tensorrt`, and `rknn`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
Frigate provides the following builtin detector types: `cpu`, `edgetpu`, `openvino`, `tensorrt`, `rknn`, and `hailo8l`. By default, Frigate will use a single CPU detector. Other detectors may require additional configuration as described below. When using multiple detectors they will run in dedicated processes, but pull from a common queue of detection requests from across all cameras.
## CPU Detector (not recommended)
@@ -386,3 +386,25 @@ $ cat /sys/kernel/debug/rknpu/load
- All models are automatically downloaded and stored in the folder `config/model_cache/rknn_cache`. After upgrading Frigate, you should remove older models to free up space.
- You can also provide your own `.rknn` model. You should not save your own models in the `rknn_cache` folder, store them directly in the `model_cache` folder or another subfolder. To convert a model to `.rknn` format see the `rknn-toolkit2` (requires a x86 machine). Note, that there is only post-processing for the supported models.
## Hailo-8l
This detector is available if you are using the Raspberry Pi 5 with Hailo-8L AI Kit. This has not been tested using the Hailo-8L with other hardware.
### Configuration
```yaml
detectors:
hailo8l:
type: hailo8l
device: PCIe
model:
path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
model:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
model_type: ssd
```