Roboflow Python Library
Website • Docs • Blog • Twitter • Linkedin • Universe
Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless. This is the official Roboflow python package that interfaces with the Roboflow API. Key features of Roboflow:
- Import and Export image datasets into any supported formats
- Preprocess and augment data using Roboflow's dataset management tools
- Train computer vision models using Roboflow Train and deploy to production
- Use community curated projects to start building your own vision-powered products
Installation:
To install this package, please use Python 3.6 or higher. We provide three different ways to install the Roboflow
package to use within your own projects.
Install from PyPi (Recommended):
pip install roboflow
Install from Source:
git clone https://github.com/roboflow-ai/roboflow-python.git
cd roboflow-python
python3 -m venv
source venv/bin/activate
pip3 install -r requirements.txt
Quickstart
import roboflow
# Instantiate Roboflow object with your API key
rf = roboflow.Roboflow(api_key=YOUR_API_KEY_HERE)
# List all projects for your workspace
workspace = rf.workspace()
# Load a certain project, workspace url is optional
project = rf.project("PROJECT_ID")
# List all versions of a specific project
project.versions()
# Upload image to dataset
project.upload("UPLOAD_IMAGE.jpg")
# Retrieve the model of a specific project
project.version("1").model
# predict on a local image
prediction = model.predict("YOUR_IMAGE.jpg")
# Predict on a hosted image
prediction = model.predict("YOUR_IMAGE.jpg", hosted=True)
# Plot the prediction
prediction.plot()
# Convert predictions to JSON
prediction.json()
# Save the prediction as an image
prediction.save(output_path='predictions.jpg')
Metadata
Release files for roboflow 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| roboflow-0.1.3.tar.gz | 14.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| roboflow-0.1.3-py2-none-any.whl | Python 2 | none | any | Details |
Total release size: 37.7 kB
Release files / roboflow-0.1.3.tar.gz
| Download URL | roboflow-0.1.3.tar.gz |
|---|---|
| Size | 14.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fd85097518eab0d809a5c3c3ee4ec73b021f4de7969953b225a7c9e7003afb21
|
|
BLAKE2b-256 checksum How to use checksums |
2e329af459b78694ac716076a4d3c2369b5d6582c3c81663d9fd7bbb3e5dd8dd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.4
|
Release files / roboflow-0.1.3-py2-none-any.whl
| Download URL | roboflow-0.1.3-py2-none-any.whl |
|---|---|
| Size | 23.6 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
21fdb76ba8df0bbf9b2ce67ae1b4cbcb7a115dbd3cba2ee5abdf6580a9524954
|
|
BLAKE2b-256 checksum How to use checksums |
5f22300a6ee58f57c39041054f5b845d5bfb324cb77c52e86e794a57c3f10c92
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.4
|