YOLOv8解决图像分类完整源码+数据（大作业）.zip

# Ultralytics requirements # Example: pip install -r requirements.txt # Base ---------------------------------------- matplotlib>=3.2.2 numpy>=1.22.2 # pinned by Snyk to avoid a vulnerability opencv-python>=4.6.0 pillow>=7.1.2 pyyaml>=5.3.1 requests>=2.23.0 scipy>=1.4.1 torch>=1.8.0 torchvision>=0.9.0 tqdm>=4.64.0 # Logging ------------------------------------- # tensorboard>=2.13.0 # dvclive>=2.12.0 # clearml # comet # Plotting ------------------------------------ pandas>=1.1.4 seaborn>=0.11.0 # Export -------------------------------------- # coremltools>=7.0.b1 # CoreML export # onnx>=1.12.0 # ONNX export # onnxsim>=0.4.1 # ONNX simplifier # nvidia-pyindex # TensorRT export # nvidia-tensorrt # TensorRT export # scikit-learn==0.19.2 # CoreML quantization # tensorflow>=2.4.1 # TF exports (-cpu, -aarch64, -macos) # tflite-support # tensorflowjs>=3.9.0 # TF.js export # openvino-dev>=2023.0 # OpenVINO export # Extras -------------------------------------- psutil # system utilization py-cpuinfo # display CPU info # thop>=0.1.1 # FLOPs computation # ipython # interactive notebook # albumentations>=1.0.3 # training augmentations # pycocotools>=2.0.6 # COCO mAP # roboflow