super-resolution
TrainYourOwnYOLO
| super-resolution | TrainYourOwnYOLO | |
|---|---|---|
| 2 | 1 | |
| 1,452 | 635 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | over 1 year ago | |
| Python | Jupyter Notebook | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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super-resolution
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Is it not possible to get good results in Deep Learning if dataset is small (1000 images)? [D]
https://github.com/krasserm/super-resolution (Super useful for me)
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How to train "models" for opensv edsr (iam super noob)
And thanks ! so it means that I need to train it with one of these trainers inside this project for example https://github.com/krasserm/super-resolution And that means that iam forced to use python (at least for training) but it's OK 🙃
TrainYourOwnYOLO
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help calculating AP for yolov3 on matlab also my recall precision plot looks jank, more info in comments
Hey, so im pretty new to this and used https://github.com/AntonMu/TrainYourOwnYOLO to train a yolov3 model for pedestrian detection. I'm using the kitti object detection dataset.
What are some alternatives?
Fast-SRGAN - A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
SSD-Mobilenet-Custom-Object-Detector-Model-using-Tensorflow-2 - This repository contains the script and process to create custom SSD Mobilenet model for object detection
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
colabcat - :smiley_cat: Running Hashcat on Google Colab with session backup and restore.
SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
tf2patcher - A patcher for TF2 that allows you to apply full-colored decals.
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
pix2seq - Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
CleanTF2plus - Clean TF2's sequel
SinGAN - Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
YOLOv3-Cloud-Based-Fire-Detection - Custom Object detection using YOLOv3 on the cloud. It is trained to detect Fire in a given frame. It can be largely used for Wildfires, fire accidents, etc.