Push model using huggingface_hub.

README.md

@@ -1,45 +1,9 @@
 ---
-license: agpl-3.0
 tags:
-- object-detection
-- computer-vision
-- yolov10
-datasets:
-- detection-datasets/coco
+- pytorch_model_hub_mixin
+- model_hub_mixin
 ---
 
-### Model Description
-[YOLOv10: Real-Time End-to-End Object Detection](https://arxiv.org/abs/2405.14458v1)
-
-- arXiv: https://arxiv.org/abs/2405.14458v1
-- github: https://github.com/THU-MIG/yolov10
-
-### Installation
-```
-pip install supervision git+https://github.com/THU-MIG/yolov10.git
-```
-
-### Yolov10 Inference
-```python
-from ultralytics import YOLOv10
-import supervision as sv
-import cv2
-
-IMAGE_PATH = 'dog.jpeg'
-
-model = YOLOv10.from_pretrained('jameslahm/yolov10s')
-model.predict(IMAGE_PATH, show=True)
-
-# after training, one can push to the hub
-model.push_to_hub("your-hf-username/yolov10-finetuned")
-```
-
-### BibTeX Entry and Citation Info
- ```
-@article{wang2024yolov10,
-  title={YOLOv10: Real-Time End-to-End Object Detection},
-  author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang},
-  journal={arXiv preprint arXiv:2405.14458},
-  year={2024}
-}
-```
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Library: [More Information Needed]
+- Docs: [More Information Needed]

config.json

@@ -1,3 +1,86 @@
 {
-  "model": "yolov10s.yaml"
+  "model": "yolov10s.yaml",
+  "names": {
+    "0": "person",
+    "1": "bicycle",
+    "2": "car",
+    "3": "motorcycle",
+    "4": "airplane",
+    "5": "bus",
+    "6": "train",
+    "7": "truck",
+    "8": "boat",
+    "9": "traffic light",
+    "10": "fire hydrant",
+    "11": "stop sign",
+    "12": "parking meter",
+    "13": "bench",
+    "14": "bird",
+    "15": "cat",
+    "16": "dog",
+    "17": "horse",
+    "18": "sheep",
+    "19": "cow",
+    "20": "elephant",
+    "21": "bear",
+    "22": "zebra",
+    "23": "giraffe",
+    "24": "backpack",
+    "25": "umbrella",
+    "26": "handbag",
+    "27": "tie",
+    "28": "suitcase",
+    "29": "frisbee",
+    "30": "skis",
+    "31": "snowboard",
+    "32": "sports ball",
+    "33": "kite",
+    "34": "baseball bat",
+    "35": "baseball glove",
+    "36": "skateboard",
+    "37": "surfboard",
+    "38": "tennis racket",
+    "39": "bottle",
+    "40": "wine glass",
+    "41": "cup",
+    "42": "fork",
+    "43": "knife",
+    "44": "spoon",
+    "45": "bowl",
+    "46": "banana",
+    "47": "apple",
+    "48": "sandwich",
+    "49": "orange",
+    "50": "broccoli",
+    "51": "carrot",
+    "52": "hot dog",
+    "53": "pizza",
+    "54": "donut",
+    "55": "cake",
+    "56": "chair",
+    "57": "couch",
+    "58": "potted plant",
+    "59": "bed",
+    "60": "dining table",
+    "61": "toilet",
+    "62": "tv",
+    "63": "laptop",
+    "64": "mouse",
+    "65": "remote",
+    "66": "keyboard",
+    "67": "cell phone",
+    "68": "microwave",
+    "69": "oven",
+    "70": "toaster",
+    "71": "sink",
+    "72": "refrigerator",
+    "73": "book",
+    "74": "clock",
+    "75": "vase",
+    "76": "scissors",
+    "77": "teddy bear",
+    "78": "hair drier",
+    "79": "toothbrush"
+  },
+  "task": "detect"
 }