Add YOLO-Seg

README.md

@@ -4,6 +4,7 @@ NVIDIA DeepStream SDK 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1  configuration
 
 --------------------------------------------------------------------------------------------------
 ### YOLO-Pose: https://github.com/marcoslucianops/DeepStream-Yolo-Pose
+### YOLO-Seg: https://github.com/marcoslucianops/DeepStream-Yolo-Seg
 --------------------------------------------------------------------------------------------------
 ### Important: please export the ONNX model with the new export file, generate the TensorRT engine again with the updated files, and use the new config_infer_primary file according to your model
 --------------------------------------------------------------------------------------------------
@@ -29,13 +30,14 @@ NVIDIA DeepStream SDK 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1  configuration
 * INT8 calibration (PTQ) for Darknet and ONNX exported models
 * New output structure (fix wrong output on DeepStream < 6.2) - it need to export the ONNX model with the new export file, generate the TensorRT engine again with the updated files, and use the new config_infer_primary file according to your model
 * **YOLO-Pose: https://github.com/marcoslucianops/DeepStream-Yolo-Pose**
+* **YOLO-Seg: https://github.com/marcoslucianops/DeepStream-Yolo-Seg**
 
 ##
 
 ### Getting started
 
 * [Requirements](#requirements)
-* [Suported models](#supported-models)
+* [Supported models](#supported-models)
 * [Benchmarks](docs/benchmarks.md)
 * [dGPU installation](docs/dGPUInstalation.md)
 * [Basic usage](#basic-usage)
@@ -156,7 +158,7 @@ NVIDIA DeepStream SDK 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1  configuration
 
 ##
 
-### Suported models
+### Supported models
 
 * [Darknet](https://github.com/AlexeyAB/darknet)
 * [MobileNet-YOLO](https://github.com/dog-qiuqiu/MobileNet-Yolo)

docs/DAMOYOLO.md

@@ -166,6 +166,7 @@ parse-bbox-func-name=NvDsInferParseYoloE
 **NOTE**: The **DAMO-YOLO** do not resize the input with padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=0
 ...
@@ -174,6 +175,7 @@ maintain-aspect-ratio=0
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/PPYOLOE.md

@@ -145,6 +145,7 @@ parse-bbox-func-name=NvDsInferParseYoloE
 **NOTE**: The **PP-YOLOE+ and PP-YOLOE legacy** do not resize the input with padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=0
 ...
@@ -153,6 +154,7 @@ maintain-aspect-ratio=0
 **NOTE**: The **PP-YOLOE+** uses zero mean normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
 
 ```
+[property]
 ...
 net-scale-factor=0.0039215697906911373
 ...
@@ -163,6 +165,7 @@ net-scale-factor=0.0039215697906911373
 Default: `mean = 0.485, 0.456, 0.406` and `std = 0.229, 0.224, 0.225`
 
 ```
+[property]
 ...
 net-scale-factor=0.0173520735727919486
 offsets=123.675;116.28;103.53
@@ -172,6 +175,7 @@ offsets=123.675;116.28;103.53
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLONAS.md

@@ -201,6 +201,7 @@ parse-bbox-func-name=NvDsInferParseYoloE
 **NOTE**: The **YOLO-NAS** resizes the input with left/top padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=0
@@ -210,6 +211,7 @@ symmetric-padding=0
 **NOTE**: The **pre-trained YOLO-NAS** uses zero mean normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
 
 ```
+[property]
 ...
 net-scale-factor=0.0039215697906911373
 ...
@@ -218,6 +220,7 @@ net-scale-factor=0.0039215697906911373
 **NOTE**: The **custom YOLO-NAS** uses no normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
 
 ```
+[property]
 ...
 net-scale-factor=1
 ...
@@ -226,6 +229,7 @@ net-scale-factor=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOR.md

@@ -184,6 +184,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOR** resizes the input with center padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=1
@@ -193,6 +194,7 @@ symmetric-padding=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOX.md

@@ -150,6 +150,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOX and YOLOX legacy** resize the input with left/top padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=0
@@ -159,6 +160,7 @@ symmetric-padding=0
 **NOTE**: The **YOLOX** uses no normalization on the image preprocess. It is important to change the `net-scale-factor` according to the trained values.
 
 ```
+[property]
 ...
 net-scale-factor=1
 ...
@@ -169,6 +171,7 @@ net-scale-factor=1
 Default: `mean = 0.485, 0.456, 0.406` and `std = 0.229, 0.224, 0.225`
 
 ```
+[property]
 ...
 net-scale-factor=0.0173520735727919486
 offsets=123.675;116.28;103.53
@@ -178,6 +181,7 @@ offsets=123.675;116.28;103.53
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOv5.md

@@ -176,6 +176,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOv5** resizes the input with center padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=1
@@ -185,6 +186,7 @@ symmetric-padding=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOv6.md

@@ -176,6 +176,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOv6** resizes the input with center padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=1
@@ -185,6 +186,7 @@ symmetric-padding=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOv7.md

@@ -178,6 +178,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOv7** resizes the input with center padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=1
@@ -187,6 +188,7 @@ symmetric-padding=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...

docs/YOLOv8.md

@@ -169,6 +169,7 @@ parse-bbox-func-name=NvDsInferParseYolo
 **NOTE**: The **YOLOv8** resizes the input with center padding. To get better accuracy, use
 
 ```
+[property]
 ...
 maintain-aspect-ratio=1
 symmetric-padding=1
@@ -178,6 +179,7 @@ symmetric-padding=1
 **NOTE**: By default, the dynamic batch-size is set. To use implicit batch-size, uncomment the line
 
 ```
+[property]
 ...
 force-implicit-batch-dim=1
 ...