DarkPlate
DarkHelp
DarkPlate | DarkHelp | |
---|---|---|
6 | 7 | |
53 | 131 | |
- | - | |
0.0 | 8.6 | |
about 1 year ago | 10 days ago | |
C++ | C++ | |
MIT License | MIT License |
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DarkPlate
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Need Help to Design an OCR for number plate test extraction
Take a look at DarkPlate, which can process either videos or static images: https://github.com/stephanecharette/DarkPlate
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Help with video data for custom yolov3 model
This is how I would do it: https://github.com/stephanecharette/DarkPlate
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I have a set of images with instances of two classes are labeled on it. Can I train Yolo V5 or V4 to detect both classes on a test image?
Here is an example project with 37 classes, and all the images are within the same folder: https://github.com/stephanecharette/DarkPlate/tree/master/nn
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What is the best way to process video frames in darknet for YOLO object detection?
1) At the very bottom of this page: https://www.ccoderun.ca/darkhelp/api/API.html 2) This example github project: https://github.com/stephanecharette/DarkPlate
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What are some of the best models/approaches for number plate recognition?
I use YOLOv4-tiny. I make two passes with the same neural network. First pass to find the plate, 2nd pass to read the characters. Demo (skip to 86 seconds): https://www.youtube.com/watch?v=jz97_-PCxl4&t=86s and code: https://github.com/stephanecharette/DarkPlate
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need advice on a opencv project [Question] [Project]
See here for example, where frames are extracted and then passed to the neural network for processing: https://github.com/stephanecharette/DarkPlate/blob/master/src/main.cpp#L216-L217
DarkHelp
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Tips for making an Object Tracking Dataset
The code is open-source. The project starts with this: https://github.com/stephanecharette/DarkHelp/blob/master/src-apps/video_object_counter.cpp
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Yolov7 with c++
In my repo (https://github.com/stephanecharette/DarkHelp) I say that? Please show me where.
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Trim YOLO / darknet video?
From your description: I'd use the MoveDetect library to find where movement occurs, and then feed just those frames or videos into DarkHelp. Note that DarkHelp also has much richer JSON output than the vanilla Darknet CLI.
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Why is c++ compiling so damn hard?
Came here to say the same. I work mostly on embedded devices, OpenCV, ML/CV type of products. And all our cmake files use globbing, and we love it. Here is an example CMake file for an open source tool I publish on github: https://github.com/stephanecharette/DarkHelp/blob/master/src-lib/CMakeLists.txt
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Object detection CV models for CPU
I use the darknet C++ API, DarkHelp. But to be fair and in the spirit of full disclosure...I wrote it. :)
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Looking for “Computer vision, darknet yolo expert to run code on multi-GPU server”
(I'm the author of DarkHelp, the C++ layer for Darknet.)
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Annotating and detecting objects in a video
DarkHelp will load videos, run inference, and create a new output video. https://github.com/stephanecharette/DarkHelp
What are some alternatives?
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
pydensecrf - Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs with gaussian edge potentials.
deep-license-plate-recognition - Automatic License Plate Recognition (ALPR) or Automatic Number Plate Recognition (ANPR) software that works with any camera.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
Pine - :evergreen_tree: Aimbot powered by real-time object detection with neural networks, GPU accelerated with Nvidia. Optimized for use with CS:GO.
DarkMark - Marking up images for use with Darknet.
anpr - Issue tracker e documentazione di ANPR - Anagrafe Nazionale della Popolazione Residente
darknet_ros - YOLO ROS: Real-Time Object Detection for ROS
MoveDetect - Library to detect whether movement can be detected between two images or video frames.
evoke - Magic build tool