Instructions to use maju116/yolo3-coco-keras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use maju116/yolo3-coco-keras with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://maju116/yolo3-coco-keras") - Notebooks
- Google Colab
- Kaggle
YOLOv3 COCO โ Keras 3
YOLOv3 object detection model trained on COCO dataset.
Framework
- Keras 3
- TensorFlow backend
Input
- Shape:
(416, 416, 3) - RGB images, values in
[0, 1]or[0, 255]
Output
Model returns three tensors:
grid1:(13, 13, 3, 85)grid2:(26, 26, 3, 85)grid3:(52, 52, 3, 85)
(85 = 4 bbox + 1 objectness + 80 classes)
Load example
from keras.models import load_model
model = load_model("coco_yolo_v3.keras", compile=False)
- Downloads last month
- 18
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐ Ask for provider support