|
| 1 | +import os |
| 2 | +import sys |
| 3 | + |
| 4 | +thisdir = os.path.dirname(os.path.abspath(__file__)) |
| 5 | +os.environ["ROBOFLOW_CONFIG_DIR"] = f"{thisdir}/data/.config" |
| 6 | + |
| 7 | +from roboflow.roboflowpy import _argparser # noqa: E402 |
| 8 | +from roboflow import Roboflow |
| 9 | + |
| 10 | +# import requests |
| 11 | +# requests.urllib3.disable_warnings() |
| 12 | + |
| 13 | +rootdir = os.path.abspath(f"{thisdir}/../..") |
| 14 | +sys.path.append(rootdir) |
| 15 | + |
| 16 | + |
| 17 | +def run_cli(): |
| 18 | + parser = _argparser() |
| 19 | + # args = parser.parse_args(["login"]) |
| 20 | + # args = parser.parse_args(f"upload {thisdir}/../datasets/chess -w wolfodorpythontests -p chess".split()) # noqa: E501 // docs |
| 21 | + args = parser.parse_args( |
| 22 | + # ["login"] |
| 23 | + "download -f yolov8 https://universe.roboflow.com/gdit/aerial-airport".split() |
| 24 | + # "project list -w wolfodorpythontests".split() |
| 25 | + # "project get cultura-pepino-dark".split() |
| 26 | + # "workspace list".split() |
| 27 | + # "workspace get wolfodorpythontests".split() |
| 28 | + # f"infer -w jacob-solawetz -m rock-paper-scissors-slim/5 -c .01 {thisdir}/data/scissors.png".split() # noqa: E501 // docs |
| 29 | + # f"infer -w roboflow-6tyri -m usa-states/3 -c .94 -t instance-segmentation {thisdir}/data/unitedstates.jpg".split() # noqa: E501 // docs |
| 30 | + # f"infer -w naumov-igor-segmentation -m car-segmetarion/2 -t semantic-segmentation {thisdir}/data/car.jpg".split() # noqa: E501 // docs |
| 31 | + # f"import {thisdir}/data/cultura-pepino-voc -w wolfodorpythontests -p cultura-pepino-voc -c 50".split() # noqa: E501 // docs |
| 32 | + # f"import {thisdir}/data/0311fisheye -w wolfodorpythontests -p 0311fisheye -c 50".split() # noqa: E501 // docs |
| 33 | + # f"upload {thisdir}/data/cultura-pepino-darknet/train/10_jpg.rf.2b3a401b0ffd8482e52137ad22faa14f.jpg -a {thisdir}/data/cultura-pepino-darknet/train/10_jpg.rf.2b3a401b0ffd8482e52137ad22faa14f.txt -m {thisdir}/data/cultura-pepino-darknet/train/_darknet.labels -w wolfodorpythontests -p cultura-pepino-darknet -r 3".split() # noqa: E501 // docs |
| 34 | + # f"upload -p ordered-uploading {thisdir}/data/ordered-upload/1.jpg".split() |
| 35 | + # f"import -p ordered-uploading {thisdir}/data/ordered-upload".split() |
| 36 | + # f"import -p yellow-auto {thisdir}/data/ordered-upload".split() |
| 37 | + # f" {thisdir}/data/cultura-pepino-darknet -w wolfodorpythontests -p cultura-pepino-darknet -c 100".split() # noqa: E501 // docs |
| 38 | + # f"import {thisdir}/data/cultura-pepino-darknet -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 39 | + # f"import {thisdir}/data/cultura-pepino-clip -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 40 | + # f"import {thisdir}/data/cultura-pepino-voc -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 41 | + # f"import {thisdir}/data/cultura-pepino-coco -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 42 | + # f"import {thisdir}/data/cultura-pepino-yolov8 -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 43 | + # f"import {thisdir}/data/cultura-pepino-yolov8_voc -w wolfodorpythontests -p yellow-auto -c 100".split() # noqa: E501 // docs |
| 44 | + # f"import {thisdir}/data/cultura-pepino-yolov5pytorch -w wolfodorpythontests -p yellow-auto -c 100 -n papaiasso".split() # noqa: E501 // docs |
| 45 | + # f"import {thisdir}/../datasets/mosquitos -w wolfodorpythontests -p yellow-auto -n papaiasso".split() # noqa: E501 // docs |
| 46 | + # f"deployment list".split() # noqa: E501 // docs |
| 47 | + # f"import -w tonyprivate -p meh-plvrv {thisdir}/../datasets/paligemma/".split() # noqa: E501 // docs |
| 48 | + ) |
| 49 | + args.func(args) |
| 50 | + |
| 51 | + |
| 52 | +def run_api_train(): |
| 53 | + rf = Roboflow() |
| 54 | + project = rf.workspace("model-evaluation-workspace").project("penguin-finder") |
| 55 | + # version_number = project.generate_version( |
| 56 | + # settings={ |
| 57 | + # "augmentation": { |
| 58 | + # "bbblur": {"pixels": 1.5}, |
| 59 | + # "image": {"versions": 2}, |
| 60 | + # }, |
| 61 | + # "preprocessing": { |
| 62 | + # "auto-orient": True, |
| 63 | + # }, |
| 64 | + # } |
| 65 | + # ) |
| 66 | + version_number = "18" |
| 67 | + print(version_number) |
| 68 | + version = project.version(version_number) |
| 69 | + model = version.train( |
| 70 | + speed="fast", # Options: "fast" (default) or "accurate" (paid feature) |
| 71 | + checkpoint=None, # Use a specific checkpoint to continue training |
| 72 | + modelType="rfdetr-nano", |
| 73 | + ) |
| 74 | + print(model) |
| 75 | + |
| 76 | + |
| 77 | +if __name__ == "__main__": |
| 78 | + # run_cli() |
| 79 | + run_api_train() |
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