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Hi. How can I change the thickness of bounding boxes on the images during inference? I have high-resolution images, and the bounding box that I am getting is too thin and barely visible. It also seems like the text size for class labels on images changes based on the size of the detected bounding box. Is there a way to correct this?
Environment
sys.platform: linux
Python: 3.8.19 (default, Mar 20 2024, 19:58:24) [GCC 11.2.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0: NVIDIA RTX 2000 Ada Generation Laptop GPU
CUDA_HOME: /usr/local/cuda-12.1
NVCC: Cuda compilation tools, release 12.1, V12.1.66
GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.0.0+cu117
PyTorch compiling details: PyTorch built with:
GCC 9.3
C++ Version: 201703
Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
Prerequisite
🐞 Describe the bug
Hi. How can I change the thickness of bounding boxes on the images during inference? I have high-resolution images, and the bounding box that I am getting is too thin and barely visible. It also seems like the text size for class labels on images changes based on the size of the detected bounding box. Is there a way to correct this?
Environment
sys.platform: linux
Python: 3.8.19 (default, Mar 20 2024, 19:58:24) [GCC 11.2.0]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0: NVIDIA RTX 2000 Ada Generation Laptop GPU
CUDA_HOME: /usr/local/cuda-12.1
NVCC: Cuda compilation tools, release 12.1, V12.1.66
GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.0.0+cu117
PyTorch compiling details: PyTorch built with:
OpenCV: 4.9.0
MMEngine: 0.10.4
MMCV: 2.0.1
MMDetection: 3.3.0
MMYOLO: 0.6.0+8c4d9dc
Additional information
No response
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