This article compares two methods for detecting and removing watermarks. Comment A focuses on video watermarks using specific transforms/models, while Comment B emphasizes local contrast enhancement for subtle watermark detection improvements.

Video delogo/inpainting

propainter remove watermark with tracking, entity segmentation

you can use clip for watermark detection, but you don’t know where. fuck. you better train it yourself.

watermark detection model

import timm
# all other pytorch imports
# Not used but necessary when running on images
transforms = T.Compose([
T.Resize((256, 256)),
T.ToTensor(),
T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])
])
# Create model
model = timm.create_model('efficientnet_b3a', pretrained=False, num_classes=2)
model.classifier = nn.Sequential(
nn.Linear(in_features=1536, out_features=625),
nn.ReLU(),
nn.Dropout(p=0.3),
nn.Linear(in_features=625, out_features=256),
nn.ReLU(),
nn.Linear(in_features=256, out_features=2)
)
# Load model weights
state_dict = torch.load('./model.pt')
model.load_state_dict(state_dict).eval().to(device)
# Sample Image
im = torch.randn(8, 3, 256, 256)
with torch.no_grad():
pred = model(im)
syms = F.softmax(pred, dim=1).detach().cpu().numpy().tolist()
for water_sym, clear_sym in syms:
# Do whatever you want with the watermark simlarity

image local contrast enhancement, for removing hard-to-detect watermarks

maybe you can use the same trick (context preserving sliding window) from your search engine to here (image preprocessing)!

paddleocr识别效果最好可以识别水印位置以及文字

Linear Contrast Stretching, HE, AHE, CLAHE of an image using matlab

Histogram Equalization (HE)

Adaptive Histogram Equalization (AHE)

Contrast Limited Adaptive Histogram Equalisation (CLAHE)

experiment path:

pyjom/tests/remove_subtle_watermark_local_contrast_ocr

bing query for image local contrast

darktable lua api and scripting

darktable local contrast darktable is an open-sourced photography postprocessing software

configurations:

details: 443
highlights: 36
shadows: 25
midtone range: 0.16

imagej clahe local contrast enhancement

l2uwe L^2UWE: A Framework for the Efficient Enhancement of Low-Light Underwater Images Using Local Contrast and Multi-Scale Fusion written in matlab

glcae Global and Local Contrast Adaptive Enhancement for Non-uniform Illumination Color Images in python

CNN-Based-X-ray-Morphological-Decomposition

github query for local image contrast

image processing basics Image Reading, writing, histogram, histogram equalization, local histogram equalization, low pass filter, high pass filter, geometrical transformation

contrast normalization is an implementation that applies local contrast normalization to images in matlab

contrast enhancement as a github topic

mclahe NumPy and Tensorflow implementation of the Multidimensional Contrast Limited Adaptive Histogram Equalization (MCLAHE) procedure

deepcontrast A deep learning-based fully-automatic intravenous contrast detection tool for head-and-neck and chest CT scans.

mirnetv2 (TPAMI 2022) Learning Enriched Features for Fast Image Restoration and Enhancement. Results on Defocus Deblurring, Denoising, Super-resolution, and image enhancement

pymusica is a contrast enhancement approach involving non linear mapping of Laplacian pyramid.

imWeightedThresholdedheq attempts to enhance contrast of a given image or video by employing a method called weighted thresholded histogram equalization (WTHE).

imagemagick wand local_contrast function

dual gamma clahe Automatic Contrast-Limited Adaptive Histogram Equalization With Dual Gamma Correction

imhblpce attempts to enhance contrast of a given image by employing a method called HBLPCE.

matlab localcontrast for image