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Author:
Roboflow
Summary:
With no prior knowledge of machine learning or device-specific deployment, you can deploy a computer vision model to a range of devices and environments using Roboflow Inference.
Latest version:
0.62.2
Required dependencies:
aiohttp
|
aiortc
|
anthropic
|
apscheduler
|
asyncua
|
backoff
|
boto3
|
cachetools
|
click
|
cython
|
dataclasses-json
|
docker
|
fastapi
|
filelock
|
httpx
|
inference-exp
|
networkx
|
numpy
|
nvidia-ml-py
|
onnxruntime
|
onvif-zeep-async
|
openai
|
opencv-contrib-python
|
opencv-python
|
packaging
|
paho-mqtt
|
pandas
|
pillow
|
prometheus-fastapi-instrumentator
|
psutil
|
py-cpuinfo
|
pybase64
|
pydantic
|
pydantic-settings
|
pydot
|
pylogix
|
pymodbus
|
pytest
|
python-dotenv
|
pyyaml
|
qrcode
|
redis
|
requests
|
requests-toolbelt
|
rich
|
scikit-image
|
setuptools
|
shapely
|
simple-pid
|
slack-sdk
|
structlog
|
supervision
|
tldextract
|
tokenizers
|
tqdm
|
twilio
|
typer
|
typing_extensions
|
wheel
|
zxing-cpp
Optional dependencies:
accelerate
|
asgi_correlation_id
|
bitsandbytes
|
dill
|
easyocr
|
einops
|
elasticache_auto_discovery
|
fastapi-cprofile
|
mediapipe
|
num2words
|
orjson
|
peft
|
pycocotools
|
pymemcache
|
python-multipart
|
pyvips
|
rasterio
|
rf-clip
|
rf-segment-anything
|
rf_groundingdino
|
samv2
|
timm
|
torch
|
torchvision
|
transformers
|
ultralytics
|
uvicorn
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