v0.9.17
馃殌 Added
YOLOWorld - new versions and Roboflow hosted inference 馃く
inference package now support 5 new versions of YOLOWorld model. We've added versions x, v2-s, v2-m, v2-l, v2-x. Versions with prefix v2 have better performance than the previously published ones.
To use YOLOWorld in inference, use the following model_id: yolo_world/<version>, substituting <version> with one of [s, m, l, x, v2-s, v2-m, v2-l, v2-x].
You can use the models in different contexts:
Roboflow hosted inference - easiest way to get your predictions 馃挜
馃挕 Please make sure you have inference-sdk installed
If you do not have the whole inference package installed, you will need to install at leastinference-sdk:
pip install inference-sdk馃挕 You need Roboflow account to use our hosted platform
import cv2
from inference_sdk import InferenceHTTPClient
client = InferenceHTTPClient(api_url="https://infer.roboflow.com", api_key="<YOUR_ROBOFLOW_API_KEY>")
image = cv2.imread("<path_to_your_image>")
results = client.infer_from_yolo_world(
image,
["person", "backpack", "dog", "eye", "nose", "ear", "tongue"],
model_version="s", # <-- you do not need to provide `yolo_world/` prefix here
)Self-hosted inference server
馃挕 Please remember to clean up old version of docker image
If you ever used inference server before, please run:
docker rmi roboflow/roboflow-inference-server-cpu:latest
# or, if you have GPU on the machine
docker rmi roboflow/roboflow-inference-server-gpu:latestin order to make sure the newest version of image is pulled.
馃挕 Please make sure you run the server and have sdk installed
If you do not have the whole inference package installed, you will need to install at least inference-cli and inference-sdk:
pip install inference-sdk inference-cliMake sure you start local instance of inference server before running the code
inference server startimport cv2
from inference_sdk import InferenceHTTPClient
client = InferenceHTTPClient(api_url="http:https://127.0.0.1:9001")
image = cv2.imread("<path_to_your_image>")
results = client.infer_from_yolo_world(
image,
["person", "backpack", "dog", "eye", "nose", "ear", "tongue"],
model_version="s", # <-- you do not need to provide `yolo_world/` prefix here
)In inference Python package
馃挕 Please remember to install inference with yolo-world extras
pip install "inference[yolo-world]"import cv2
from inference.models import YOLOWorld
image = cv2.imread("<path_to_your_image>")
model = YOLOWorld(model_id="yolo_world/s")
results = model.infer(
image,
["person", "backpack", "dog", "eye", "nose", "ear", "tongue"]
)
馃尡 Changed
- Track source for remote execution flows by @tonylampada in #320
- Improved documentation by @capjamesg in #321
New Contributors
- @tonylampada made their first contribution in #320 馃
Full Changelog: v0.9.16...v0.9.17
