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EasyCV/tests/ut_config.py
gulou 645fed2d1b
add data source and support for automatic download (#206) 
* add data_source imagenet

* modify data_source imagenet and add unittest

* modify data_source imagenet and modify unittest

* modify voc data_source and modify voc unittest and download Part

* modify coco data_source and modify coco unittest and  add download Part , modify voc data_source

* add dataset metadata Format specification

* add pose download data , modify coco.py and modiy download file function ,add test coco download a part

* modify download file function

* modify download of cifar10 and cifar100

* modify dataset_name  to target_dir

* create download_util and modify function

* modify function

* modify function

* add test case , modify

* modify something

* modify something

* modify something

* modify something

* modify something

* modify something

* add wget

* add wget

* modify

* add new modify

* add new modify

* modify something

* modify something and add something

* modify something and add something

* modify something and add something

* modify something and add something

* modify something and add something

* modify test case

* modify test case

* modify test case

* modify test case

* modify test case
2022-11-04 19:36:37 +08:00

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import os
IMG_NORM_CFG_255 = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
IMG_NORM_CFG = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
COCO_CLASSES = [
'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train',
'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign',
'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag',
'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sports ball', 'kite',
'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon',
'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot',
'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'potted plant',
'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote',
'keyboard', 'cell phone', 'microwave', 'oven', 'toaster', 'sink',
'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
'hair drier', 'toothbrush'
]
VOC_CLASSES = [
'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat',
'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person',
'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'
]
NUSCENES_CLASSES = [
'car', 'truck', 'construction_vehicle', 'bus', 'trailer', 'barrier',
'motorcycle', 'bicycle', 'pedestrian', 'traffic_cone'
]
BASE_OSS_PATH = 'oss://pai-vision-data-hz/unittest/'
BASE_LOCAL_PATH = os.path.expanduser('~/easycv_nfs/')
TMP_DIR_OSS = os.path.join(BASE_OSS_PATH, 'tmp')
TMP_DIR_LOCAL = os.path.join(BASE_LOCAL_PATH, 'tmp')
CLS_DATA_NPY_LOCAL = os.path.join(BASE_LOCAL_PATH, 'data/classification/npy/')
SMALL_IMAGENET_RAW_LOCAL = os.path.join(
BASE_LOCAL_PATH, 'data/classification/small_imagenet_raw')
CIFAR10_LOCAL = os.path.join(BASE_LOCAL_PATH, 'data/classification/cifar10')
CIFAR100_LOCAL = os.path.join(BASE_LOCAL_PATH, 'data/classification/cifar100')
SAMLL_IMAGENET1K_RAW_LOCAL = os.path.join(BASE_LOCAL_PATH,
'datasets/imagenet-1k/imagenet_raw')
SMALL_IMAGENET_TFRECORD_LOCAL = os.path.join(
BASE_LOCAL_PATH, 'data/classification/small_imagenet_tfrecord/')
IMAGENET_LABEL_TXT = os.path.join(
BASE_LOCAL_PATH, 'data/classification/imagenet/imagenet_label.txt')
CLS_DATA_NPY_OSS = os.path.join(BASE_OSS_PATH, 'data/classification/npy/')
SMALL_IMAGENET_TFRECORD_OSS = os.path.join(
BASE_OSS_PATH, 'data/classification/small_imagenet_tfrecord/')
IO_DATA_TXTX_OSS = os.path.join(BASE_OSS_PATH, 'data/io_test_dir/txts/')
IO_DATA_MULTI_DIRS_OSS = os.path.join(BASE_OSS_PATH,
'data/io_test_dir/multi_dirs/')
DET_DATA_SMALL_COCO_LOCAL = os.path.join(BASE_LOCAL_PATH,
'data/detection/small_coco')
DET_DATA_COCO2017_DOWNLOAD = os.path.join(BASE_LOCAL_PATH, 'download_local/')
VOC_DATASET_DOWNLOAD_LOCAL = os.path.join(BASE_LOCAL_PATH, 'download_local')
VOC_DATASET_DOWNLOAD_SMALL = os.path.join(BASE_LOCAL_PATH,
'download_local/small_download')
COCO_DATASET_DOWNLOAD_SMALL = os.path.join(BASE_LOCAL_PATH,
'download_local/small_download')
CONFIG_PATH = 'configs/detection/yolox/yolox_s_8xb16_300e_coco.py'
DET_DATA_RAW_LOCAL = os.path.join(BASE_LOCAL_PATH, 'data/detection/raw_data')
DET_DATA_SMALL_VOC_LOCAL = os.path.join(BASE_LOCAL_PATH,
'data/detection/small_voc')
DET_DATA_MANIFEST_OSS = os.path.join(BASE_OSS_PATH,
'data/detection/small_coco_itag')
POSE_DATA_SMALL_COCO_LOCAL = os.path.join(BASE_LOCAL_PATH,
'data/pose/small_coco')
SSL_SMALL_IMAGENET_FEATURE = os.path.join(
BASE_LOCAL_PATH, 'data/selfsup/small_imagenet_feature')
SSL_SMALL_IMAGENET_RAW = os.path.join(BASE_LOCAL_PATH,
'data/selfsup/small_imagenet')
TEST_IMAGES_DIR = os.path.join(BASE_LOCAL_PATH, 'data/test_images')
COMPRESSION_TEST_DATA = os.path.join(BASE_LOCAL_PATH,
'data/compression/test_data')
SEG_DATA_SMALL_RAW_LOCAL = os.path.join(BASE_LOCAL_PATH,
'data/segmentation/small_voc_200')
# OCR data
SMALL_OCR_CLS_DATA = os.path.join(BASE_LOCAL_PATH, 'data/ocr/small_ocr_cls')
SMALL_OCR_DET_DATA = os.path.join(BASE_LOCAL_PATH, 'data/ocr/small_ocr_det')
SMALL_OCR_DET_PAI_DATA = os.path.join(BASE_LOCAL_PATH,
'data/ocr/small_ocr_det_pai')
SMALL_OCR_REC_DATA = os.path.join(BASE_LOCAL_PATH, 'data/ocr/small_ocr_rec')
PRETRAINED_MODEL_MOCO = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/selfsup/moco/moco_epoch_200.pth')
PRETRAINED_MODEL_RESNET50 = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/classification/resnet/resnet50.pth')
PRETRAINED_MODEL_RESNET50_WITHOUTHEAD = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/classification/resnet/resnet50_withhead.pth')
PRETRAINED_MODEL_FACEID = os.path.join(BASE_LOCAL_PATH,
'pretrained_models/faceid')
PRETRAINED_MODEL_YOLOXS_EXPORT = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/detection/infer_yolox/epoch_300.pt')
PRETRAINED_MODEL_YOLOXS_EXPORT_OLD = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/detection/infer_yolox/old.pt')
PRETRAINED_MODEL_YOLOXS_NOPRE_NOTRT_JIT = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_nopre_notrt_e2e.pt.jit')
PRETRAINED_MODEL_YOLOXS_PRE_NOTRT_JIT = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_pre_notrt_e2e.pt.jit')
PRETRAINED_MODEL_YOLOXS_PRE_NOTRT_JIT_B2 = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_pre_notrt_e2e_b2.pt.jit'
)
PRETRAINED_MODEL_YOLOXS_NOPRE_TRT_JIT = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_nopre_trt.pt.jit')
PRETRAINED_MODEL_YOLOXS_PRE_TRT_JIT = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_pre_trt.pt.jit')
PRETRAINED_MODEL_YOLOXS_NOPRE_NOTRT_BLADE = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_nopre_notrt.pt.blade')
PRETRAINED_MODEL_YOLOXS_PRE_NOTRT_BLADE = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_pre_notrt.pt.blade')
PRETRAINED_MODEL_YOLOXS_NOPRE_TRT_BLADE = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_nopre_trt.pt.blade')
PRETRAINED_MODEL_YOLOXS_PRE_TRT_BLADE = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection/infer_yolox/epoch_300_pre_trt.pt.blade')
PRETRAINED_MODEL_YOLOXS = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/detection/infer_yolox/epoch_300.pth')
PRETRAINED_MODEL_POSE_HRNET_EXPORT = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/pose/hrnet/pose_hrnet_epoch_210_export.pt')
PRETRAINED_MODEL_YOLOX_COMPRESSION = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/compression/yolox_compression.pth')
PRETRAINED_MODEL_MAE = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/classification/vit/mae_vit_b_1600.pth')
PRETRAINED_MODEL_MASK2FORMER_DIR = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/segmentation/mask2former/')
PRETRAINED_MODEL_MASK2FORMER = os.path.join(PRETRAINED_MODEL_MASK2FORMER_DIR,
'mask2former_r50_instance.pth')
PRETRAINED_MODEL_OCRDET = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/ocr/det/student_export.pth')
PRETRAINED_MODEL_OCRREC = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/ocr/rec/best_accuracy_student_export.pth')
PRETRAINED_MODEL_OCRCLS = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/ocr/cls/best_accuracy_export.pth')
PRETRAINED_MODEL_SEGFORMER = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/segmentation/segformer/segformer_b0/SegmentationEvaluator_mIoU_best.pth'
)
PRETRAINED_MODEL_BEVFORMER_BASE = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/detection3d/bevformer/bevformer_base_epoch_24.pth')
PRETRAINED_MODEL_FACE_2D_KEYPOINTS = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/face_2d_keypoints/epoch_400.pth')
PRETRAINED_MODEL_HAND_KEYPOINTS = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/pose/hand/hrnet/hrnet_w18_256x256.pth')
PRETRAINED_MODEL_WHOLEBODY_DETECTION = os.path.join(
BASE_LOCAL_PATH, 'pretrained_models/pose/wholebody/epoch_290.pth')
PRETRAINED_MODEL_WHOLEBODY = os.path.join(
BASE_LOCAL_PATH,
'pretrained_models/pose/wholebody/hrnet_w48_coco_wholebody_384x288_dark-f5726563_20200918.pth'
)
MODEL_CONFIG_SEGFORMER = (
'./configs/segmentation/segformer/segformer_b0_coco.py')
SMALL_COCO_WHOLE_BODY_HAND_ROOT = 'data/test/pose/hand/small_whole_body_hand_coco'
SMALL_NUSCENES_PATH = os.path.join(
BASE_LOCAL_PATH, 'data/detection3d/nuScenes/nuscenes-v1.0-mini')
SMALL_COCO_WHOLEBODY_ROOT = 'data/test/pose/wholebody/data'
MODEL_CONFIG_MASK2FORMER_PAN = (
'./configs/segmentation/mask2former/mask2former_r50_8xb2_e50_panoptic.py')
MODEL_CONFIG_MASK2FORMER_INS = (
'./configs/segmentation/mask2former/mask2former_r50_8xb2_e50_instance.py')
MODEL_CONFIG_MASK2FORMER_SEM = (
'./configs/segmentation/mask2former/mask2former_r50_8xb2_e127_semantic.py')
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