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You are reading the documentation for MMEditing 0.x, which will soon be deprecated by the end of 2022. We recommend you upgrade to MMEditing 1.0 to enjoy fruitful new features and better performance brought by OpenMMLab 2.0. Check out the changelog, code and documentation of MMEditing 1.0 for more details.

Demo

We provide some task-specific demo scripts to test a single image.

Inpainting

You can use the following commands to test a pair of images for inpainting.

python demo/inpainting_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${MASKED_IMAGE_FILE} \
    ${MASK_FILE} \
    ${SAVE_FILE} \
    [--imshow] \
    [--device ${GPU_ID}]

If --imshow is specified, the demo will also show image with opencv. Examples:

python demo/inpainting_demo.py \
    configs/inpainting/global_local/gl_256x256_8x12_celeba.py \
    https://download.openmmlab.com/mmediting/inpainting/global_local/gl_256x256_8x12_celeba_20200619-5af0493f.pth \
    tests/data/image/celeba_test.png \
    tests/data/image/bbox_mask.png \
    tests/data/pred/inpainting_celeba.png

The predicted inpainting result will be save in tests/data/pred/inpainting_celeba.png.

Matting

You can use the following commands to test a pair of images and trimap.

python demo/matting_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${IMAGE_FILE} \
    ${TRIMAP_FILE} \
    ${SAVE_FILE} \
    [--imshow] \
    [--device ${GPU_ID}]

If --imshow is specified, the demo will also show image with opencv. Examples:

python demo/matting_demo.py \
    configs/mattors/dim/dim_stage3_v16_pln_1x1_1000k_comp1k.py \
    work_dirs/dim_stage3/latest.pth \
    tests/data/merged/GT05.jpg \
    tests/data/trimap/GT05.png \
    tests/data/pred/GT05.png

The predicted alpha matte will be save in tests/data/pred/GT05.png.

Restoration (Image)

You can use the following commands to test an image for restoration.

python demo/restoration_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${IMAGE_FILE} \
    ${SAVE_FILE} \
    [--imshow] \
    [--device ${GPU_ID}] \
    [--ref-path ${REF_PATH}]

If --imshow is specified, the demo will also show image with opencv. Examples:

python demo/restoration_demo.py \
    configs/restorers/esrgan/esrgan_x4c64b23g32_g1_400k_div2k.py \
    work_dirs/esrgan_x4c64b23g32_g1_400k_div2k/latest.pth \
    tests/data/lq/baboon_x4.png \
    demo/demo_out_baboon.png

You can test Ref-SR by providing --ref-path. Examples:

python demo/restoration_demo.py \
    configs/restorers/ttsr/ttsr-gan_x4_c64b16_g1_500k_CUFED.py \
    https://download.openmmlab.com/mmediting/restorers/ttsr/ttsr-gan_x4_c64b16_g1_500k_CUFED_20210626-2ab28ca0.pth \
    tests/data/test_multiple_gt/sequence_1/00000000.png \
    work_dirs/demo_out.png \
    --ref-path tests/data/test_multiple_gt/sequence_1/00000001.png

Restoration (Face Image)

You can use the following commands to test an face image for restoration.

python demo/restoration_face_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${IMAGE_FILE} \
    ${SAVE_FILE} \
    [--upscale-factor] \
    [--face-size] \
    [--imshow] \
    [--device ${GPU_ID}]

If --imshow is specified, the demo will also show image with opencv. Examples:

python demo/restoration_face_demo.py \
    configs/restorers/glean/glean_in128out1024_4x2_300k_ffhq_celebahq.py \
    https://download.openmmlab.com/mmediting/restorers/glean/glean_in128out1024_4x2_300k_ffhq_celebahq_20210812-acbcb04f.pth \
    tests/data/face/000001.png \
    results/000001.png \
    --upscale-factor 4

Restoration (Video)

You can use the following commands to test a video for restoration.

python demo/restoration_video_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${INPUT_DIR} \
    ${OUTPUT_DIR} \
    [--window-size=${WINDOW_SIZE}] \
    [--device ${GPU_ID}]

It supports both the sliding-window framework and the recurrent framework. Examples:

EDVR:

python demo/restoration_video_demo.py \
    ./configs/restorers/edvr/edvrm_wotsa_x4_g8_600k_reds.py \
    https://download.openmmlab.com/mmediting/restorers/edvr/edvrm_wotsa_x4_8x4_600k_reds_20200522-0570e567.pth \
    data/Vid4/BIx4/calendar/ \
    ./output \
    --window-size=5

BasicVSR:

python demo/restoration_video_demo.py \
    ./configs/restorers/basicvsr/basicvsr_reds4.py \
    https://download.openmmlab.com/mmediting/restorers/basicvsr/basicvsr_reds4_20120409-0e599677.pth \
    data/Vid4/BIx4/calendar/ \
    ./output

The restored video will be save in output/.

video frame interpolation

You can use the following commands to test a video for frame interpolation.

python demo/video_interpolation_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${INPUT_DIR} \
    ${OUTPUT_DIR} \
    [--fps-multiplier ${FPS_MULTIPLIER}] \
    [--fps ${FPS}]

${INPUT_DIR} / ${OUTPUT_DIR} can be a path of video file or the folder of a sequence of ordered images. If ${OUTPUT_DIR} is a path of video file, its frame rate can be determined by the frame rate of input video and fps_multiplier, or be determined by fps directly (the former has higher priority). Examples:

The frame rate of output video is determined by the frame rate of input video and fps_multiplier

python demo/video_interpolation_demo.py \
    configs/video_interpolators/cain/cain_b5_320k_vimeo-triplet.py \
    https://download.openmmlab.com/mmediting/video_interpolators/cain/cain_b5_320k_vimeo-triple_20220117-647f3de2.pth \
    tests/data/test_inference.mp4 \
    tests/data/test_inference_vfi_out.mp4 \
    --fps-multiplier 2.0

The frame rate of output video is determined by fps:

python demo/video_interpolation_demo.py \
    configs/video_interpolators/cain/cain_b5_320k_vimeo-triplet.py \
    https://download.openmmlab.com/mmediting/video_interpolators/cain/cain_b5_320k_vimeo-triple_20220117-647f3de2.pth \
    tests/data/test_inference.mp4 \
    tests/data/test_inference_vfi_out.mp4 \
    --fps 60.0

Generation

python demo/generation_demo.py \
    ${CONFIG_FILE} \
    ${CHECKPOINT_FILE} \
    ${IMAGE_FILE} \
    ${SAVE_FILE} \
    [--unpaired-path ${UNPAIRED_IMAGE_FILE}] \
    [--imshow] \
    [--device ${GPU_ID}]

If --unpaired-path is specified (used for CycleGAN), the model will perform unpaired image-to-image translation. If --imshow is specified, the demo will also show image with opencv. Examples:

Paired:

python demo/generation_demo.py \
    configs/example_config.py \
    work_dirs/example_exp/example_model_20200202.pth \
    demo/demo.jpg \
    demo/demo_out.jpg

Unpaired (also show image with opencv):

python demo/generation_demo.py 、
    configs/example_config.py \
    work_dirs/example_exp/example_model_20200202.pth \
    demo/demo.jpg \
    demo/demo_out.jpg \
    --unpaired-path demo/demo_unpaired.jpg \
    --imshow
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