Build production-ready computer vision models faster. From image annotation to model training and deployment — VisionFlow is your complete CV pipeline.
From data collection to model deployment, VisionFlow handles every step of your CV pipeline.
Bounding boxes, polygons, segmentation masks, keypoints — with AI-assisted labeling that speeds up your workflow 10x.
Version your datasets, split into train/val/test, apply augmentations, and export in COCO, YOLO, or VOC format.
Train YOLOv8, classification, and segmentation models with one click. Monitor metrics in real-time.
Deploy trained models as API endpoints. Support for ONNX, TensorRT, CoreML, and TFLite formats.
Invite team members, assign annotation tasks, review labels, and track progress across projects.
Full REST API with SDKs for Python and JavaScript. Integrate VisionFlow into your existing pipeline.
Support for the latest YOLO models and transformer-based detectors.
Integrate VisionFlow into your pipeline with 3 lines of code.
pip install visionflowfrom visionflow import VisionFlowClient
vf = VisionFlowClient(api_key="vf_xxx")
# Train a model
job = vf.train_and_wait(
project_id=1,
model="yolov8n",
epochs=50
)
# Run inference
result = vf.predict(
deployment_id=1,
image="photo.jpg"
)
print(result["predictions"])Join thousands of ML engineers using VisionFlow to ship computer vision faster.