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https://github.com/open-mmlab/mmdeploy.git
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fd75d57175
* add ncnn test exporter in test_ops.py * add ncnn test exporter in utils.py * add onnxruntime and tensorrt ops test * fix blank line * fix comment add nms ops test * remove nms test * add test sample add dockerstring * remove nms test * fix grid_sample add type hind * fix problem * fix dockerstring * add nms batch_nms multi_level_roi_align * add test data * fix problem * rm pkl file dependent * rm file * add docstring * remove multi_level_dependce * add mmseg module unittest * add mmseg test * add mmseg model unit test * fix blankline * rename file * add syncbn2bn unit test * add apis/export * lint * lint * ?? * delete# * fix ncnn check * fix problems * fix problems * fix dim problems * resolve comments * Fix SwitchBackendWrapper * fix assert problems * fix assert * Remove comment * merge master Co-authored-by: SingleZombie <singlezombie@163.com>
98 lines
3.2 KiB
Python
98 lines
3.2 KiB
Python
import mmcv
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import numpy as np
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from mmdeploy.apis.utils import build_dataloader, build_dataset, create_input
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from mmdeploy.utils.constants import Codebase, Task
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class TestCreateInput:
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task = Task.SUPER_RESOLUTION
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img_test_pipeline = [
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dict(
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type='LoadImageFromFile',
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io_backend='disk',
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key='lq',
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flag='unchanged'),
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dict(
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type='LoadImageFromFile',
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io_backend='disk',
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key='gt',
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flag='unchanged'),
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dict(type='RescaleToZeroOne', keys=['lq', 'gt']),
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dict(
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type='Normalize',
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keys=['lq', 'gt'],
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mean=[0, 0, 0],
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std=[1, 1, 1],
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to_rgb=True),
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dict(
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type='Collect',
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keys=['lq', 'gt'],
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meta_keys=['lq_path', 'lq_path']),
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dict(type='ImageToTensor', keys=['lq', 'gt'])
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]
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imgs = np.random.rand(32, 32, 3)
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img_path = 'tests/test_mmedit/data/imgs/blank.jpg'
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def test_create_input_static(self):
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data = dict(test=dict(pipeline=TestCreateInput.img_test_pipeline))
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model_cfg = mmcv.Config(
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dict(data=data, test_pipeline=TestCreateInput.img_test_pipeline))
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inputs = create_input(
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Codebase.MMEDIT,
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TestCreateInput.task,
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model_cfg,
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TestCreateInput.imgs,
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input_shape=(32, 32),
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device='cpu')
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assert inputs is not None, 'Failed to create input'
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def test_create_input_dynamic(self):
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data = dict(test=dict(pipeline=TestCreateInput.img_test_pipeline))
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model_cfg = mmcv.Config(
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dict(data=data, test_pipeline=TestCreateInput.img_test_pipeline))
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inputs = create_input(
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Codebase.MMEDIT,
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TestCreateInput.task,
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model_cfg,
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TestCreateInput.imgs,
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input_shape=None,
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device='cpu')
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assert inputs is not None, 'Failed to create input'
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def test_create_input_from_file(self):
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data = dict(test=dict(pipeline=TestCreateInput.img_test_pipeline))
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model_cfg = mmcv.Config(
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dict(data=data, test_pipeline=TestCreateInput.img_test_pipeline))
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inputs = create_input(
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Codebase.MMEDIT,
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TestCreateInput.task,
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model_cfg,
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TestCreateInput.img_path,
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input_shape=None,
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device='cpu')
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assert inputs is not None, 'Failed to create input'
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def test_build_dataset():
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data = dict(
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test={
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'type': 'SRFolderDataset',
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'lq_folder': 'tests/test_mmedit/data/imgs',
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'gt_folder': 'tests/test_mmedit/data/imgs',
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'scale': 1,
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'filename_tmpl': '{}',
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'pipeline': [
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{
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'type': 'LoadImageFromFile'
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},
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]
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})
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dataset_cfg = mmcv.Config(dict(data=data))
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dataset = build_dataset(
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Codebase.MMEDIT, dataset_cfg=dataset_cfg, dataset_type='test')
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assert dataset is not None, 'Failed to build dataset'
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dataloader = build_dataloader(Codebase.MMEDIT, dataset, 1, 1)
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assert dataloader is not None, 'Failed to build dataloader'
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