Discover @oleksandr-g-rock Open Source projects

Oleksandr G. (@oleksandr-g-rock)

oleksandr-g-rock

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Global Rank 242,014 (Top 9 %)
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Registered about 7 years ago
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Python
72.7 %

Jupyter Notebook
22.7 %

Shell
4.5 %
Location 🇬🇧 United Kingdom
Country Total Rank 11,262
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Jupyter Notebook
667

Python
2,905

Shell
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How_to_create_confusion_matrix

How to create a confusion matrix with the test result in your training model & How to visualize the history of network learning: accuracy, loss in graphs.

Jupyter Notebook

How_to_create-image-classification-for-recognizing-persons-animals-others

Create image classification for recognizing persons, animals, others.

Jupyter Notebook

flower_classification

Image Classifications: Flowers Recognition

Jupyter Notebook

how_to_convert_h5_model_to_tflite

How to convert h5 model to tflite model

Jupyter Notebook

image_classification_pi_camera_live_time_custom_model_tflite

Image classification (persons, animals, other) on raspberry pi from pi-camera (in live time) used custom model tflite (output to terminal)

How-to-divide-image-4-part-using-OpenCV

How to divide the image into 4 parts using OpenCV

Quantization

Quantization (post-training quantization) your (custom mobilenet_v2) models .h5 or .pb models using TensorFlow Lite 2.4

classify_picamera_in_live_time_cusom_model

Image classification (persons, animals, other) on raspberry pi from pi-camera (in live time) used custom model .h5 (output to terminal)

simple_classification_pi_vgg16_pretrain_model

Simple image classification on raspberry pi used the pre-trained model VGG16

simple_classification_pi_vgg16_pretrain_model_from_pi_camera

Simple image classification on raspberry pi from pi-camera used the pre-trained model VGG16

install_packages_for_pi_nn

classify_picamera_with_while_cusom_model

Image classification (persons, animals, other) on raspberry pi from pi-camera (with cycle while) used custom model .h5 (output to terminal)

simple_classification_pi_vgg16_pretrain_model_from_pi_camera_while

Simple image classification on raspberry pi from pi-camera (with cycle while) used the pre-trained model VGG16

simple_object_detection

Create simple recognition object detection in the live time on the Raspberry Pi - version 2

oleksandr-g-rock

live-time-used-custom-model-tflite-dividing-image-into-4

image_lassify_tflite_simple

Simple image classification (persons, animals, other) on raspberry pi used custom model tflite (output to terminal)

create_animation_graphs_in_python

How to create live animation graphs in python

image_classification_out_to_terminal

Simple image classification on raspberry pi from pi-camera (in live time) used the pre-trained model mobilenet_v1 and TensorFlow Lite (output to terminal)

custom_object_detection_person_notperson

image_classify_tflite_camera_pi_while

Image classification (persons, animals, other) on raspberry pi from pi-camera (with cycle while) used custom tflite model (output to terminal)

simple-image-classification-4-divide-image-tflite

Simple image classification (persons, animals, other) on raspberry pi used custom model tflite (output to terminal) dividing image into 4 parts using OpenCV and TensorFlow Lite

disease-recognition-from-xray

Recognition (3 diseases) from X-ray (Machine Learning tutorial) with accuracy: 96%

Jupyter Notebook