feat: add more detection models

README.md

@@ -39,20 +39,26 @@ In addition, some models can be evaluated directly through [Akida Cloud](https:/
 | Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/trail_camera)| 224        | Trail_camera  | 2.43M   | 8            | 84.74%   |          |       | 6 ☁️         |
 | Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/road_signs)  | 224        | Road_signs    | 2.43M   | 8            | 65.46%   |          |       | 6 ☁️         |
 | Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/furniture)   | 224        | Furniture     | 2.43M   | 8            | 79.21%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/aerial-cows)        | 384        | aerial-cows          | 2.43M   | 8            | 30.91%   |          |       | 16         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/bees)               | 224        | bees                 | 2.43M   | 8            | 59.99%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/cable-damage)       | 224        | cable-damage         | 2.43M   | 8            | 77.32%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/corrosion)          | 224        | corrosion            | 2.43M   | 8            | 39.06%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/digits)             | 224        | digits               | 2.43M   | 8            | 92.32%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/face_detection)     | 224        | face detection       | 2.43M   | 8            | 75.98%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/hand-gestures)      | 224        | hand-gestures        | 2.43M   | 8            | 53.52%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/license_plate_detection)      | 224        | License plate        | 2.43M   | 8            | 96.22%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/liver-disease)      | 224        | liver-disease        | 2.43M   | 8            | 40.57%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/phages)             | 224        | phages               | 2.43M   | 8            | 67.18%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/sign-language)      | 224        | sign-language        | 2.43M   | 8            | 85.88%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/stomata-cells)      | 224        | stomata-cells        | 2.43M   | 8            | 52.14%   |          |       | 6 ☁️         |
-| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/underwater-objects) | 224        | underwater-objects   | 2.43M   | 8            | 44.89%   |          |       | 6 ☁️         |
-
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/aerial-cows)        | 384        | Aerial_Cows          | 2.43M   | 8            | 30.91%   |          |       | 16         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/bees)               | 224        | Bees                 | 2.43M   | 8            | 59.99%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/cable-damage)       | 224        | Cable_Damage         | 2.43M   | 8            | 77.32%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/corrosion)          | 224        | Corrosion            | 2.43M   | 8            | 39.06%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/digits)             | 224        | Digits               | 2.43M   | 8            | 92.32%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/face_detection)     | 224        | Face_Detection       | 2.43M   | 8            | 75.98%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/hand-gestures)      | 224        | Hand_Gestures        | 2.43M   | 8            | 53.52%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/license_plate_detection)      | 224        | License_Plate        | 2.43M   | 8            | 96.22%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/liver-disease)      | 224        | Liver_Disease        | 2.43M   | 8            | 40.57%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/phages)             | 224        | Phages               | 2.43M   | 8            | 67.18%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/sign-language)      | 224        | Sign_Language        | 2.43M   | 8            | 85.88%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/stomata-cells)      | 224        | Stomata_Cells        | 2.43M   | 8            | 52.14%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/underwater-objects) | 224        | Underwater_Objects   | 2.43M   | 8            | 44.89%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/abs_obb)            | 384        | Ships_Detection      | 2.43M   | 8            | 39.60%   |          |       | 12         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/bone_fracture)      | 224        | Bone_Fracture        | 2.43M   | 8            | 60.70%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/facial_expression)  | 224        | Facial_Expression    | 2.43M   | 8            | 75.40%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/pothole_detection)  | 224        | Pothole_Detection    | 2.43M   | 8            | 57.20%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/search_and_rescue)  | 224        | Search_And_Rescue    | 2.43M   | 8            | 77.00%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/traffic_detection)  | 224        | Traffic_Detection    | 2.43M   | 8            | 71.80%   |          |       | 6 ☁️         |
+| Vision        | Detection         | [AkidaNet18/CenterNet](vision/detection/akidanet18_centernet/weed_crop)          | 384        | Weed_Crop            | 2.43M   | 8            | 47.70%   |          |       | 16          |
 
 ## Download
 ### Git Clone

vision/detection/akidanet18_centernet/abs_obb/README.md

@@ -0,0 +1,20 @@
+#  AkidaNet18/CenterNet (Custom Model)
+
+## Source
+This model uses the pre-trained base model centernet_akidanet18_voc_384.h5 from our data center: [**centernet_akidanet18_voc_384**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+- **Backbone**: AkidaNet18 backbone
+- **Head**: CenterNet
+
+## Environment
+```
+tf_keras: 2.19
+cnn2snn: 2.17.0
+quantizeml: 1.0.1
+```
+
+## References
+- **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
+- **Dataset**: [ships detection (private)]()
+
+## License
+Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/aerial_cows/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_384.h5 from our data center: [**centernet_akidanet18_voc_384**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [aerial cows detection](https://universe.roboflow.com/roboflow-100/aerial-cows/dataset/2)
+- **Dataset**: [aerial cows detection](https://universe.roboflow.com/roboflow-100/aerial-cows/dataset/2)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/bees/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [bees detection](https://universe.roboflow.com/roboflow-100/bees-jt5in/dataset/2)
+- **Dataset**: [bees detection](https://universe.roboflow.com/roboflow-100/bees-jt5in/dataset/2)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/bone_fracture/README.md

@@ -0,0 +1,20 @@
+#  AkidaNet18/CenterNet (Custom Model)
+
+## Source
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
+- **Backbone**: AkidaNet18 backbone
+- **Head**: CenterNet
+
+## Environment
+```
+tf_keras: 2.19
+cnn2snn: 2.17.0
+quantizeml: 1.0.1
+```
+
+## References
+- **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
+- **Dataset**: [bone fracture detection](https://www.kaggle.com/datasets/ranaamahmudd22/bone-fracture-detection-v1i-yolov8)
+
+## License
+Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/cable_damage/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [cable damage detection](https://universe.roboflow.com/roboflow-100/cable-damage/dataset/2)
+- **Dataset**: [cable damage detection](https://universe.roboflow.com/roboflow-100/cable-damage/dataset/2)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/corrosion/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [corrosion detection](https://universe.roboflow.com/roboflow-100/corrosion-bi3q3/dataset/2)
+- **Dataset**: [corrosion detection](https://universe.roboflow.com/roboflow-100/corrosion-bi3q3/dataset/2)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/digits/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [digits detection](https://universe.roboflow.com/roboflow-100/digits-t2eg6/dataset/2)
+- **Dataset**: [digits detection](https://universe.roboflow.com/roboflow-100/digits-t2eg6/dataset/2)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/face_detection/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [face detection](https://universe.roboflow.com/mohamed-traore-2ekkp/face-detection-mik1i/dataset/20)
+- **Dataset**: [face detection](https://universe.roboflow.com/mohamed-traore-2ekkp/face-detection-mik1i/dataset/20)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/facial_expression/README.md

@@ -0,0 +1,20 @@
+#  AkidaNet18/CenterNet (Custom Model)
+
+## Source
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
+- **Backbone**: AkidaNet18 backbone
+- **Head**: CenterNet
+
+## Environment
+```
+tf_keras: 2.19
+cnn2snn: 2.17.0
+quantizeml: 1.0.1
+```
+
+## References
+- **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
+- **Dataset**: [facial expression detection](https://www.kaggle.com/datasets/fatihkgg/affectnet-yolo-format)
+
+## License
+Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/furniture/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [furniture detection](https://universe.roboflow.com/projet-ai/furniture-azcxt/dataset/1)
+- **Dataset**: [furniture detection](https://universe.roboflow.com/projet-ai/furniture-azcxt/dataset/1)
 
 ## License
 Apache 2.0 License (models only)

vision/detection/akidanet18_centernet/hand_gestures/README.md

@@ -1,7 +1,7 @@
 #  AkidaNet18/CenterNet (Custom Model)
 
 ## Source
-This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_384.h5)
+This model uses the pre-trained base model centernet_akidanet18_voc_224.h5 from our data center: [**centernet_akidanet18_voc_224**](https://data.brainchip.com/models/AkidaV2/centernet/centernet_akidanet18_voc_224.h5)
 - **Backbone**: AkidaNet18 backbone
 - **Head**: CenterNet
 
@@ -14,7 +14,7 @@ quantizeml: 1.0.1
 
 ## References
 - **AkidaNet18**: Akida model API [AkidaNet18 architecture](https://doc.brainchipinc.com/api_reference/akida_models_apis.html#akida_models.akidanet18_imagenet)
-- **Dataset**:  [hand gestures detection](https://universe.roboflow.com/roboflow-100/hand-gestures-jps7z/dataset/2)
+- **Dataset**: [hand gestures detection](https://universe.roboflow.com/roboflow-100/hand-gestures-jps7z/dataset/2)
 
 ## License
 Apache 2.0 License (models only)