Principle:Tencent Ncnn Image Preprocessing
| Knowledge Sources | |
|---|---|
| Domains | Computer_Vision, Preprocessing |
| Last Updated | 2026-02-09 00:00 GMT |
Overview
Process of converting raw pixel data into a normalized floating-point tensor matching a neural network's expected input format, dimensions, and value range.
Description
Image preprocessing bridges the gap between raw image data (integer pixel values in BGR/RGB format) and the floating-point tensor format expected by neural networks. The process typically involves three operations: (1) pixel format conversion (e.g., BGR to RGB), (2) spatial resizing to the model's expected input dimensions (e.g., 224x224, 640x640), and (3) mean subtraction and normalization to center the data distribution around zero and scale to a standard range.
These operations must precisely match the preprocessing used during model training. Mismatches in channel ordering, resize interpolation, mean values, or normalization scales are a common source of incorrect inference results.
Usage
Use this principle before every forward pass through a neural network. Apply it after reading the raw image and before feeding the tensor to the network's input blob. The specific preprocessing parameters (mean values, normalization scales, target size, pixel format) are model-dependent and must match the training configuration.
Theoretical Basis
The standard preprocessing pipeline for image classification and detection models:
Where:
- is the per-channel mean (e.g., ImageNet: [104, 117, 123] for BGR)
- is the per-channel normalization scale (e.g., 1/255 for [0,1] range, or 1/58.395 for ImageNet std)
Pseudo-code:
// Abstract preprocessing algorithm
image = load_image(path) // raw pixels
resized = resize(image, target_w, target_h) // bilinear interpolation
tensor = convert_to_float(resized, pixel_format) // channel reorder + float cast
for each channel c:
tensor[c] = (tensor[c] - mean[c]) * norm[c] // normalize
The resize step uses bilinear interpolation by default. Some detection models require letterbox padding (preserving aspect ratio with border padding) instead of direct resize.