MMDetection Hello World

Installation

Clone the Repository

To get started, clone this repository along with its submodule. Run the following command in your terminal:

git clone --recurse-submodules https://github.com/aklein1995/object_detection_mmdetection.git

Create Virtual Environment

python3.10 -m venv .venv

PyTorch

pip install torch==2.1.0

MMCV

MMCV is a foundational library for computer vision that supports MMDetection. Install the specific version of MMCV according to URL (check "install with pip" section to get the concrete installation command)

pip install mmcv==2.1.0 -f https://download.openmmlab.com/mmcv/dist/cu121/torch2.1/index.html

In our case, assume to have installed CUDA 12.1 and torch2.1.

MMDetection

Navigate to the mmdetection submodule directory and install MMDetection in editable mode:

cd mmdetection
pip install -v -e .

Non-Maximum Suppression (NMS)

It can be adjusted in two ways:

Modify the score threshold in the configuration file, which is usually codified in the test_cfg section:

model = dict(
    ...
    test_cfg=dict(
        nms_pre=1000,
        score_thr=0.05,  # The score threshold
        nms=dict(type='nms', iou_threshold=0.5),  # The NMS IoU threshold
        max_per_img=100)
    ...
)

Filter the output based on the scores after the detections are made:

# Define your detection threshold
detection_threshold = 0.5  # Example threshold

# Assuming 'result' is the output from 'inference_detector' and contains the bounding boxes and scores
for i, (boxes, scores) in enumerate(zip(result[0], result[1])):
    # Filter out detections with scores below the threshold
    indices = scores > detection_threshold
    filtered_boxes = boxes[indices]
    filtered_scores = scores[indices]

aklein1995 / object_detection_mmdetection