requirements.cuda.txt

# YOLOv5 requirements
# Usage: pip install -r requirements.txt

numpy<2.0                       # Installing NumPy, a package for scientific computing
urllib3<1.27,>=1.25.4           # Installing urllib3, the HTTP client for Python

# Base ----------------------------------------
matplotlib>=3.2.2               # Installing matplotlib, the python plotting package
opencv-python>=4.1.1,<=4.9      # Installing OpenCV, the Open source Computer Vision library
Pillow<10.0.0                   # Installing Pillow, a Python Image Library
PyYAML>=5.3.1                   # Installing PyYAML, a library for reading configuration files
requests>=2.23.0                # Installing request, the HTTP library
scipy>=1.4.1                    # Installing SciPy, a library for mathematics, science, and engineering

#--find-links https://download.pytorch.org/whl/cu117
#torch>=1.7.0                   # Installing Torch, for Tensor computation and Deep neural networks
#torchvision>=0.8.1             # Installing TorchVision, for Computer Vision based AI

## For CUDA 11.7
--find-links https://download.pytorch.org/whl/torch_stable.html
torch==1.13.0+cu117             # Installing PyTorch, an open source machine learning framework
--find-links https://download.pytorch.org/whl/torch_stable.html
torchvision==0.14.0+cu117       # Installing TorchVision, for working with computer vision models

tqdm>=4.64.0                    # Installing tdqm, the Fast, Extensible Progress Meter

# This is to fix an issue at https://github.com/ultralytics/yolov5/issues/8012
protobuf<=3.20.1                # Installing protobuf, extensible mechanisms for serializing structured data

# Logging -------------------------------------
tensorboard>=2.4.1              # Installing tensorboard, a tool to let you watch Tensors Flow
# wandb
# clearml

# Plotting ------------------------------------
pandas>=1.1.4                   # Installing Pandas, a data analysis / data manipulation tool
seaborn>=0.11.0                 # Installing Seaborn, a data visualization library based on matplotlib

# Export --------------------------------------
# coremltools>=5.2              # CoreML export
# onnx>=1.9.0                   # ONNX export
# onnx-simplifier>=0.4.1        # ONNX simplifier
# nvidia-pyindex                # TensorRT export
# nvidia-tensorrt               # TensorRT export
# scikit-learn==0.19.2          # CoreML quantization
# tensorflow>=2.4.1             # TFLite export (or tensorflow-cpu, tensorflow-aarch64)
# tensorflowjs>=3.9.0           # TF.js export
# openvino-dev                  # OpenVINO export

# Extras --------------------------------------
ipython                         # Installing ipython, for interactive notebooks
psutil                          # Installing psutil, a tool to check system utilization
thop>=0.1.1                     # Installing thop, a tool to count the FLOPs of PyTorch model.
# albumentations>=1.0.3
# pycocotools>=2.0              # COCO mAP
# roboflow

yolov5==6.2.3                   # Installing Ultralytics YoloV5 package for object detection in images
fiftyone                        # Installing fiftyone, for building datasets and computer vision models

CodeProject-AI-SDK              # Installing the CodeProject.AI SDK

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