initial release

2026-07-05 18:11:23 +07:00
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+This example shows how to implement YOLO object detection with ggml using pretrained model.
+
+# YOLOv3-tiny
+
+Download the model weights:
+
+```bash
+$ wget https://pjreddie.com/media/files/yolov3-tiny.weights
+$ sha1sum yolov3-tiny.weights 
+40f3c11883bef62fd850213bc14266632ed4414f  yolov3-tiny.weights
+```
+
+Convert the weights to GGUF format:
+
+```bash
+$ ./convert-yolov3-tiny.py yolov3-tiny.weights
+yolov3-tiny.weights converted to yolov3-tiny.gguf
+```
+
+Alternatively, you can download the converted model from [HuggingFace](https://huggingface.co/rgerganov/yolo-gguf/resolve/main/yolov3-tiny.gguf)
+
+Object detection:
+
+```bash
+$ wget https://raw.githubusercontent.com/pjreddie/darknet/master/data/dog.jpg
+$ ./yolov3-tiny -m yolov3-tiny.gguf -i dog.jpg
+load_model: using CUDA backend
+ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
+ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
+ggml_cuda_init: found 1 CUDA devices:
+  Device 0: NVIDIA T1200 Laptop GPU, compute capability 7.5, VMM: yes
+Layer  0 output shape:  416 x 416 x   16 x   1
+Layer  1 output shape:  208 x 208 x   16 x   1
+Layer  2 output shape:  208 x 208 x   32 x   1
+Layer  3 output shape:  104 x 104 x   32 x   1
+Layer  4 output shape:  104 x 104 x   64 x   1
+Layer  5 output shape:   52 x  52 x   64 x   1
+Layer  6 output shape:   52 x  52 x  128 x   1
+Layer  7 output shape:   26 x  26 x  128 x   1
+Layer  8 output shape:   26 x  26 x  256 x   1
+Layer  9 output shape:   13 x  13 x  256 x   1
+Layer 10 output shape:   13 x  13 x  512 x   1
+Layer 11 output shape:   13 x  13 x  512 x   1
+Layer 12 output shape:   13 x  13 x 1024 x   1
+Layer 13 output shape:   13 x  13 x  256 x   1
+Layer 14 output shape:   13 x  13 x  512 x   1
+Layer 15 output shape:   13 x  13 x  255 x   1
+Layer 18 output shape:   13 x  13 x  128 x   1
+Layer 19 output shape:   26 x  26 x  128 x   1
+Layer 20 output shape:   26 x  26 x  384 x   1
+Layer 21 output shape:   26 x  26 x  256 x   1
+Layer 22 output shape:   26 x  26 x  255 x   1
+dog: 57%
+car: 52%
+truck: 56%
+car: 62%
+bicycle: 59%
+Detected objects saved in 'predictions.jpg' (time: 0.057000 sec.)
+```