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Implement multi-model object detection

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This commit is contained in:
Nicolas Mowen
2026-07-23 17:51:21 -06:00
parent e3fa701893
commit ede06d794d
49 changed files with 1070 additions and 473 deletions
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docs/data/object_detectors_models.yaml
+236 -212
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@@ -34,12 +34,13 @@ edgeTPU:
type: edgetpu
device: usb
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize of the model, typically 320
height: 320 # <--- should match the imgsize of the model, typically 320
path: /config/model_cache/yolov9-s-relu6-best_320_int8_edgetpu.tflite
labelmap_path: /config/labels-coco17.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize of the model, typically 320
height: 320 # <--- should match the imgsize of the model, typically 320
path: /config/model_cache/yolov9-s-relu6-best_320_int8_edgetpu.tflite
labelmap_path: /config/labels-coco17.txt
hailo8l:
title: Hailo-8/Hailo-8L
models:
@@ -67,27 +68,28 @@ hailo8l:
type: hailo8l
device: PCIe
model:
width: 320
height: 320
input_tensor: nhwc
input_pixel_format: rgb
input_dtype: int
model_type: yolo-generic
labelmap_path: /labelmap/coco-80.txt
models:
default:
width: 320
height: 320
input_tensor: nhwc
input_pixel_format: rgb
input_dtype: int
model_type: yolo-generic
labelmap_path: /labelmap/coco-80.txt
# The detector automatically selects the default model based on your hardware:
# - For Hailo-8 hardware: YOLOv6n (default: yolov6n.hef)
# - For Hailo-8L hardware: YOLOv6n (default: yolov6n.hef)
#
# Optionally, you can specify a local model path to override the default.
# If a local path is provided and the file exists, it will be used instead of downloading.
# Example:
# path: /config/model_cache/hailo/yolov6n.hef
#
# You can also override using a custom URL:
# path: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ModelZoo/Compiled/v2.14.0/hailo8/yolov6n.hef
# just make sure to give it the write configuration based on the model
# The detector automatically selects the default model based on your hardware:
# - For Hailo-8 hardware: YOLOv6n (default: yolov6n.hef)
# - For Hailo-8L hardware: YOLOv6n (default: yolov6n.hef)
#
# Optionally, you can specify a local model path to override the default.
# If a local path is provided and the file exists, it will be used instead of downloading.
# Example:
# path: /config/model_cache/hailo/yolov6n.hef
#
# You can also override using a custom URL:
# path: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ModelZoo/Compiled/v2.14.0/hailo8/yolov6n.hef
# just make sure to give it the write configuration based on the model
- key: ssd
label: SSD MobileNet v1
recommended: false
@@ -111,18 +113,19 @@ hailo8l:
type: hailo8l
device: PCIe
model:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: rgb
model_type: ssd
# Specify the local model path (if available) or URL for SSD MobileNet v1.
# Example with a local path:
# path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
#
# Or override using a custom URL:
# path: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ModelZoo/Compiled/v2.14.0/hailo8l/ssd_mobilenet_v1.hef
models:
default:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: rgb
model_type: ssd
# Specify the local model path (if available) or URL for SSD MobileNet v1.
# Example with a local path:
# path: /config/model_cache/h8l_cache/ssd_mobilenet_v1.hef
#
# Or override using a custom URL:
# path: https://hailo-model-zoo.s3.eu-west-2.amazonaws.com/ModelZoo/Compiled/v2.14.0/hailo8l/ssd_mobilenet_v1.hef
openvino:
title: OpenVINO
models:
@@ -171,14 +174,15 @@ openvino:
type: openvino
device: GPU # or NPU
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: ssd
label: SSDLite MobileNet v2
recommended: false
@@ -202,13 +206,14 @@ openvino:
type: openvino
device: GPU # Or NPU
model:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
path: /openvino-model/ssdlite_mobilenet_v2.xml
labelmap_path: /openvino-model/coco_91cl_bkgr.txt
models:
default:
width: 300
height: 300
input_tensor: nhwc
input_pixel_format: bgr
path: /openvino-model/ssdlite_mobilenet_v2.xml
labelmap_path: /openvino-model/coco_91cl_bkgr.txt
- key: yolo-legacy
label: YOLO (v3, v4, v7)
recommended: false
@@ -240,14 +245,15 @@ openvino:
type: openvino
device: GPU # or NPU
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: yolonas
label: YOLO-NAS
recommended: false
@@ -280,14 +286,15 @@ openvino:
type: openvino
device: GPU
model:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_tensor: nchw
input_pixel_format: bgr
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_tensor: nchw
input_pixel_format: bgr
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
- key: yolox
label: YOLOX
recommended: false
@@ -308,10 +315,11 @@ openvino:
type: openvino
device: GPU
model:
model_type: yolox
path: /config/model_cache/yolox.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolox
path: /config/model_cache/yolox.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: rfdetr
label: RF-DETR
recommended: false
@@ -350,13 +358,14 @@ openvino:
type: openvino
device: GPU
model:
model_type: rfdetr
width: 320
height: 320
input_tensor: nchw
input_dtype: float
path: /config/model_cache/rfdetr.onnx # use the filename you generated above
models:
default:
model_type: rfdetr
width: 320
height: 320
input_tensor: nchw
input_dtype: float
path: /config/model_cache/rfdetr.onnx # use the filename you generated above
- key: dfine
label: D-FINE / DEIMv2
recommended: false
@@ -448,14 +457,15 @@ openvino:
type: openvino
device: CPU
model:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/dfine-s.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/dfine-s.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
appleSilicon:
title: Apple Silicon
models:
@@ -504,14 +514,15 @@ appleSilicon:
type: zmq
endpoint: tcp://host.docker.internal:5555
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: yolo-legacy
label: YOLO (v3, v4, v7)
recommended: false
@@ -543,14 +554,15 @@ appleSilicon:
type: zmq
endpoint: tcp://host.docker.internal:5555
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
onnx:
title: ONNX
models:
@@ -598,14 +610,15 @@ onnx:
onnx:
type: onnx
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: rfdetr
label: RF-DETR
recommended: false
@@ -643,13 +656,14 @@ onnx:
onnx:
type: onnx
model:
model_type: rfdetr
width: 320
height: 320
input_tensor: nchw
input_dtype: float
path: /config/model_cache/rfdetr.onnx # use the filename you generated above
models:
default:
model_type: rfdetr
width: 320
height: 320
input_tensor: nchw
input_dtype: float
path: /config/model_cache/rfdetr.onnx # use the filename you generated above
- key: yolonas
label: YOLO-NAS
recommended: false
@@ -681,14 +695,15 @@ onnx:
onnx:
type: onnx
model:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_pixel_format: bgr
input_tensor: nchw
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolonas
width: 320 # <--- should match whatever was set in notebook
height: 320 # <--- should match whatever was set in notebook
input_pixel_format: bgr
input_tensor: nchw
path: /config/yolo_nas_s.onnx
labelmap_path: /labelmap/coco-80.txt
- key: yolox
label: YOLOX
recommended: false
@@ -711,14 +726,15 @@ onnx:
onnx:
type: onnx
model:
model_type: yolox
width: 416 # <--- should match the imgsize set during model export
height: 416 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float_denorm
path: /config/model_cache/yolox_tiny.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolox
width: 416 # <--- should match the imgsize set during model export
height: 416 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float_denorm
path: /config/model_cache/yolox_tiny.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: dfine
label: D-FINE / DEIMv2
recommended: false
@@ -809,14 +825,15 @@ onnx:
onnx:
type: onnx
model:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/dfine_m_obj2coco.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: dfine
width: 640
height: 640
input_tensor: nchw
input_dtype: float
path: /config/model_cache/dfine_m_obj2coco.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
- key: yolo-legacy
label: YOLO (v3, v4, v7)
recommended: false
@@ -847,14 +864,15 @@ onnx:
onnx:
type: onnx
model:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
models:
default:
model_type: yolo-generic
width: 320 # <--- should match the imgsize set during model export
height: 320 # <--- should match the imgsize set during model export
input_tensor: nchw
input_dtype: float
path: /config/model_cache/yolo.onnx # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
cpu:
title: CPU
models:
@@ -928,18 +946,19 @@ memryx:
type: memryx
device: PCIe:0
model:
model_type: yolonas
width: 320 # (Can be set to 640 for higher resolution)
height: 320 # (Can be set to 640 for higher resolution)
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolonas.zip
# The .zip file must contain:
# ├── yolonas.dfp (a file ending with .dfp)
# └── yolonas_post.onnx (optional; only if the model includes a cropped post-processing network)
models:
default:
model_type: yolonas
width: 320 # (Can be set to 640 for higher resolution)
height: 320 # (Can be set to 640 for higher resolution)
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolonas.zip
# The .zip file must contain:
# ├── yolonas.dfp (a file ending with .dfp)
# └── yolonas_post.onnx (optional; only if the model includes a cropped post-processing network)
- key: yolov9
label: YOLOv9
recommended: false
@@ -965,17 +984,18 @@ memryx:
type: memryx
device: PCIe:0
model:
model_type: yolo-generic
width: 320 # (Can be set to 640 for higher resolution)
height: 320 # (Can be set to 640 for higher resolution)
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolov9.zip
# The .zip file must contain:
# ├── yolov9.dfp (a file ending with .dfp)
models:
default:
model_type: yolo-generic
width: 320 # (Can be set to 640 for higher resolution)
height: 320 # (Can be set to 640 for higher resolution)
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolov9.zip
# The .zip file must contain:
# ├── yolov9.dfp (a file ending with .dfp)
- key: yolox
label: YOLOX
recommended: false
@@ -1001,17 +1021,18 @@ memryx:
type: memryx
device: PCIe:0
model:
model_type: yolox
width: 640
height: 640
input_tensor: nchw
input_dtype: float_denorm
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolox.zip
# The .zip file must contain:
# ├── yolox.dfp (a file ending with .dfp)
models:
default:
model_type: yolox
width: 640
height: 640
input_tensor: nchw
input_dtype: float_denorm
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/yolox.zip
# The .zip file must contain:
# ├── yolox.dfp (a file ending with .dfp)
- key: ssd
label: SSDLite MobileNet v2
recommended: false
@@ -1037,18 +1058,19 @@ memryx:
type: memryx
device: PCIe:0
model:
model_type: ssd
width: 320
height: 320
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/ssdlite_mobilenet.zip
# The .zip file must contain:
# ├── ssdlite_mobilenet.dfp (a file ending with .dfp)
# └── ssdlite_mobilenet_post.onnx (optional; only if the model includes a cropped post-processing network)
models:
default:
model_type: ssd
width: 320
height: 320
input_tensor: nchw
input_dtype: float
labelmap_path: /labelmap/coco-80.txt
# Optional: The model is normally fetched through the runtime, so 'path' can be omitted unless you want to use a custom or local model.
# path: /config/ssdlite_mobilenet.zip
# The .zip file must contain:
# ├── ssdlite_mobilenet.dfp (a file ending with .dfp)
# └── ssdlite_mobilenet_post.onnx (optional; only if the model includes a cropped post-processing network)
tensorrt:
title: TensorRT
models:
@@ -1087,13 +1109,14 @@ tensorrt:
type: tensorrt
device: 0 #This is the default, select the first GPU
model:
path: /config/model_cache/tensorrt/yolov7-320.trt # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
input_tensor: nchw
input_pixel_format: rgb
width: 320 # MUST match the chosen model i.e yolov7-320 -> 320, yolov4-416 -> 416
height: 320 # MUST match the chosen model i.e yolov7-320 -> 320 yolov4-416 -> 416
models:
default:
path: /config/model_cache/tensorrt/yolov7-320.trt # use the filename you generated above
labelmap_path: /labelmap/coco-80.txt
input_tensor: nchw
input_pixel_format: rgb
width: 320 # MUST match the chosen model i.e yolov7-320 -> 320, yolov4-416 -> 416
height: 320 # MUST match the chosen model i.e yolov7-320 -> 320 yolov4-416 -> 416
synaptics:
title: Synaptics
models:
@@ -1261,14 +1284,15 @@ axengine:
axengine:
type: axengine
model:
path: frigate-yolov9-tiny
model_type: yolo-generic
width: 320
height: 320
input_dtype: int
input_pixel_format: bgr
labelmap_path: /labelmap/coco-80.txt
models:
default:
path: frigate-yolov9-tiny
model_type: yolo-generic
width: 320
height: 320
input_dtype: int
input_pixel_format: bgr
labelmap_path: /labelmap/coco-80.txt
degirumAiServer:
title: DeGirum AI Server
models: