[LEADERG AI ZOO] Jupyter-Image-Human-Pose-PyTorch
Applied to human body posture detection, it can detect the position of people's eyes, nose, ears, neck, shoulders, elbows, wrists, hip joints, knee joints, and ank
[LEADERG AI ZOO] Jupyter-Data-Dense-Stock-PyTorch
Use DenseNet to train and inference stock data.
[LEADERG AI ZOO] Jupyter-Image-GAN-Compression-PyTorch
Jupyter-Image-GAN-Compression-PyTorch is to perform style conversion after compressing the GAN model. The compressed model not only reduces the amount of calculation, r
[LEADERG AI ZOO] Jupyter-Data-Dense-Sin-PyTorch
Use DenseNet to train and inference the Sin function.
[LEADERG AI ZOO] Jupyter-Image-FaceNet
FaceNet can be applied to face grouping and face classification, and judge the similarity of faces through Euclidean distance, and then achieve face recognition.
[LEADERG AI ZOO] Jupyter-Data-Conv1D-Keras
Use one-dimensional Convolutional neural network for data analysis.
[LEADERG AI ZOO] Jupyter-GPT-2
GPT-2 is used to automatically generate an English article, and you can also enter any sentence to automatically generate an English article.
[LEADERG APP] OpenCV
The easy-to-use tools for common image processing include image reading, image saving, grayscale conversion, binarization, and connection to find objects.
[LEADERG APP] Speech2Text
The Speech2Text APP can train audio files, use the tensorflow model to analyze the selected audio files, and output its category to reach speech to text.
[LEADERG APP] Pix2Pix
The pix2pix architecture is similar to GAN, but the purpose is not to generate simulated images, but to use supervised learning to output the image style learned by the
[LEADERG APP] SuperResolution
This APP uses SRGAN to generate a High Resolution image from a Low Resolution image to improve the resolution of the image.
[LEADERG APP] CycleGAN
CycleGAN is a well-known algorithm published in ICCV2017 image-to-image translation. The biggest feature is that it does not require training data to be paired.
[LEADERG APP] HumanPose
Human body posture detection, detecting the position of human nose, eyes, ears, neck, shoulders, elbows, wrists, hip joints, knee joints, and ankles.
[LEADERG APP] FaceNet
FaceNet directly learns a mapping from face images to a compact Euclidean space where distances directly correspond to a measure of face similarity. The model does not
[LEADERG APP] Model
Model conversion, from yolo PyTorh model to ONNX model, or Tensorflow 1.X model to ONNX model.
[LEADERG APP] UNet
Use UNet for image segmentation, as shown in the figure above, which can be applied to medical image segmentation. This example is Chest CT image segmentation.
[LEADERG APP] XGBoost Regression Time Series
Use XGBoost-Regression-Time-Series to perform regression analysis of time series data.
[LEADERG APP] LSTM
Use LSTM (Long Short-Term Memory) to analyze time series data.
[LEADERG APP] CSPNet
Use CSPResNeXt50 for image classification. An example is to use steel plate defect classification. You can use this APP to train your images for image classification.
[LEADERG APP] XGBoost Classification
Use XGBoost Classification for data regression analysis.
[LEADERG APP] Annotation
This APP is an application with multiple image annotation tools. It mainly includes the common LabelImg, Labelme, the Annotation tool developed by LEADERG, and supports
[LEADERG APP] XGBoost Regression
Use XGBoost Regression for data regression analysis.
[LEADERG APP] MaskRCNN
Image segmentation with MaskRCNN.
[LEADERG APP] YOLOv4
The YOLOv4 APP can be applied to factory defect detection, medical image analysis, biological image analysis, industrial safety image analysis, mask image analysis, etc