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import the COCO Evaluator to use the COCO Metrics | |
from detectron2.config import get_cfg | |
from detectron2.engine import DefaultPredictor | |
from point_rend.config import add_pointrend_config #most important | |
from detectron2.data import build_detection_test_loader | |
from detectron2.data.datasets import register_coco_instances | |
from detectron2.evaluation import COCOEvaluator, inference_on_dataset | |
#register your data |
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import os | |
from point_rend.config import add_pointrend_config #most important | |
# from detectron2.utils.logger import setup_logger | |
# setup_logger() | |
from detectron2 import model_zoo | |
from detectron2.config import get_cfg | |
from detectron2.data.datasets import register_coco_instances | |
from detectron2.engine import DefaultTrainer | |
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import fiftyone as fo | |
import fiftyone.zoo as foz | |
dataset = foz.load_zoo_dataset("quickstart") | |
session = fo.launch_app(dataset) | |
"""Note that if you are running this code in a script, | |
you must include session.wait() to block execution until you close the App.""" | |
session.wait() |
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list_annotations = [247, 1202, 268, 1206, 262, 1232, 242, 1227, 247, 1202] | |
res = [(f , q) for f, q in zip(list_annotations[::2], list_annotations[1::2])] | |
print(res) | |
#output | |
#[(247, 1202), (268, 1206), (262, 1232), (242, 1227), (247, 1202)] |
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print(cfg.dump()) | |
with open("/code/detectron2/detectron2/output/custom_mask_rcnn_X_101_32x8d_FPN_3x_my_dataset.yaml", "w") as f: | |
f.write(cfg.dump()) |
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# -*- coding: utf-8 -*- | |
import os | |
from detectron2.utils.logger import setup_logger | |
setup_logger() | |
from detectron2 import model_zoo | |
from detectron2.config import get_cfg | |
from detectron2.data.datasets import register_coco_instances | |
from detectron2.engine import DefaultTrainer |
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#import the COCO Evaluator to use the COCO Metrics | |
from detectron2.config import get_cfg | |
from detectron2.engine import DefaultPredictor | |
from detectron2.data import build_detection_test_loader | |
from detectron2.data.datasets import register_coco_instances | |
from detectron2.evaluation import COCOEvaluator, inference_on_dataset | |
#register your data | |
register_coco_instances("my_dataset_train", {}, "/code/detectron2/detectron2/instances_train2017.json", "/code/detectron2/detectron2/train2017") | |
register_coco_instances("my_dataset_val", {}, "/code/detectron2/detectron2/instances_val2017.json", "/code/detectron2/detectron2/val2017") |
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docker run -p 9976:9976 --runtime=nvidia -e NVIDIA_VISIBLE_DEVICES=1,2 -it -v /detectron2_detection/:/code/ --name=detectron2_container detectron2:v0 |
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wget http://images.cocodataset.org/val2017/000000439715.jpg -O input.jpg |
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python3 demo/demo.py \ | |
#--config-file configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \ | |
#--input input.jpg --output outputs/ \ | |
#--opts MODEL.WEIGHTS detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl |
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