upload traj Gradio

MOFA-Video-Traj/README.md

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+## Environment Setup
+
+`pip install -r requirements.txt`
+
+## Download checkpoints
+
+1. Download the pretrained checkpoints of [SVD_xt](https://huggingface.co/stabilityai/stable-video-diffusion-img2vid-xt-1-1) from huggingface to `./ckpts`.
+
+2. Download the checkpoint of [MOFA-Adapter](https://huggingface.co/MyNiuuu/MOFA-Video-Traj) from huggingface to `./ckpts`.
+
+3. Download the checkpoint of CMP from [here](https://huggingface.co/MyNiuuu/MOFA-Video-Traj/blob/main/models/cmp/experiments/semiauto_annot/resnet50_vip%2Bmpii_liteflow/checkpoints/ckpt_iter_42000.pth.tar) and put it into `./models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/checkpoints`.
+
+The final structure of checkpoints should be:
+
+
+```text
+./ckpts/
+|-- controlnet
+|   |-- config.json
+|   `-- diffusion_pytorch_model.safetensors
+|-- stable-video-diffusion-img2vid-xt-1-1
+|   |-- feature_extractor
+|       |-- ...
+|   |-- image_encoder
+|       |-- ...
+|   |-- scheduler
+|       |-- ...
+|   |-- unet
+|       |-- ...
+|   |-- unet_ch9
+|       |-- ...
+|   |-- vae
+|       |-- ...
+|   |-- svd_xt_1_1.safetensors
+|   `-- model_index.json
+```
+
+## Run Gradio Demo
+
+`python run_gradio.py`
+
+Please refer to the instructions on the gradio interface during the inference process.

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/config.yaml

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+model:
+    arch: CMP
+    total_iter: 140000
+    lr_steps: [80000, 120000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: alexnet_fcn_32x
+        sparse_encoder: shallownet32x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 12
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [384, 384]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.000025
+    nms_ks: 81
+    max_num_guide: 150
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+        - data/youtube9000/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/resume.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/resume_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/train.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/train_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/validate.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc+youtube_voc_16gpu_140k/validate_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/config.yaml

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+model:
+    arch: CMP
+    total_iter: 70000
+    lr_steps: [40000, 60000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: alexnet_fcn_32x
+        sparse_encoder: shallownet32x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 12
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [384, 384]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.00015625
+    nms_ks: 41
+    max_num_guide: 150
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/resume.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/resume_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/train.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/train_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/validate.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_16gpu_70k/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/config.yaml

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+model:
+    arch: CMP
+    total_iter: 140000
+    lr_steps: [80000, 120000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: alexnet_fcn_32x
+        sparse_encoder: shallownet32x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 12
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [384, 384]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.00015625
+    nms_ks: 41
+    max_num_guide: 150
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/resume.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/resume_slurm.sh

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+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/train.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/train_slurm.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/validate.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/alexnet_yfcc_voc_8gpu_140k/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/config.yaml

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+model:
+    arch: CMP
+    total_iter: 70000
+    lr_steps: [40000, 60000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: resnet50
+        sparse_encoder: shallownet8x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 10
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [320, 320]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.00015625
+    nms_ks: 15
+    max_num_guide: -1
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+        - data/youtube9000/lists/train.txt
+        - data/VIP/lists/train.txt
+        - data/MPII/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/resume.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/resume_slurm.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/train.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/train_slurm.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/validate.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc+youtube+vip+mpii_lip_16gpu_70k/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/config.yaml

@@ -0,0 +1,58 @@
+model:
+    arch: CMP
+    total_iter: 42000
+    lr_steps: [24000, 36000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: resnet50
+        sparse_encoder: shallownet8x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 16
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 333
+    crop_size: [256, 256]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.00005632
+    nms_ks: 49
+    max_num_guide: -1
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/resume.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/resume_slurm.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/train.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/train_slurm.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/validate.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_coco_16gpu_42k/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/config.yaml

@@ -0,0 +1,58 @@
+model:
+    arch: CMP
+    total_iter: 42000
+    lr_steps: [24000, 36000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: resnet50
+        sparse_encoder: shallownet8x
+        flow_decoder: MotionDecoderPlain
+        skip_layer: False
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 10
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [320, 320]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 0.00003629
+    nms_ks: 67
+    max_num_guide: -1
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/yfcc/lists/train.txt
+    val_source:
+        - data/yfcc/lists/val.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 10000
+    save_freq: 10000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: False

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/resume.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/resume_slurm.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/train.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 \
+    --nnodes=2 --node_rank=$1 \
+    --master_addr="192.168.1.1" main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/train_slurm.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n16 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/validate.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/rep_learning/resnet50_yfcc_voc_16gpu_42k/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/config.yaml

@@ -0,0 +1,59 @@
+model:
+    arch: CMP
+    total_iter: 42000
+    lr_steps: [24000, 36000]
+    lr_mults: [0.1, 0.1]
+    lr: 0.1
+    optim: SGD
+    warmup_lr: []
+    warmup_steps: []
+    module:
+        arch: CMP
+        image_encoder: resnet50
+        sparse_encoder: shallownet8x
+        flow_decoder: MotionDecoderSkipLayer
+        skip_layer: True
+        img_enc_dim: 256
+        sparse_enc_dim: 16
+        output_dim: 198
+        decoder_combo: [1,2,4]
+        pretrained_image_encoder: False
+        flow_criterion: "DiscreteLoss"
+        nbins: 99
+        fmax: 50
+data:
+    workers: 2
+    batch_size: 8
+    batch_size_test: 1
+    data_mean: [123.675, 116.28, 103.53] # RGB
+    data_div: [58.395, 57.12, 57.375]
+    short_size: 416
+    crop_size: [384, 384]
+    sample_strategy: ['grid', 'watershed']
+    sample_bg_ratio: 5.74e-5
+    nms_ks: 41
+    max_num_guide: -1
+
+    flow_file_type: "jpg"
+    image_flow_aug:
+        flip: False
+    flow_aug:
+        reverse: False
+        scale: False
+        rotate: False
+    train_source:
+        - data/VIP/lists/train.txt
+        - data/MPII/lists/train.txt
+    val_source:
+        - data/VIP/lists/randval.txt
+    memcached: False
+trainer:
+    initial_val: True
+    print_freq: 100
+    val_freq: 5000
+    save_freq: 5000
+    val_iter: -1
+    val_disp_start_iter: 0
+    val_disp_end_iter: 16
+    loss_record: ['loss_flow']
+    tensorboard: True

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/resume.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 10000 \
+    --resume

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/resume_slurm.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm \
+        --load-iter 10000 \
+        --resume

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/train.sh

@@ -0,0 +1,4 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/train_slurm.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition -n8 \
+    --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py \
+        --config $work_path/config.yaml --launcher slurm

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/validate.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+work_path=$(dirname $0)
+python -m torch.distributed.launch --nproc_per_node=8 main.py \
+    --config $work_path/config.yaml --launcher pytorch \
+    --load-iter 70000 \
+    --validate

MOFA-Video-Traj/models/cmp/experiments/semiauto_annot/resnet50_vip+mpii_liteflow/validate_slurm.sh

@@ -0,0 +1,8 @@
+#!/bin/bash
+work_path=$(dirname $0)
+partition=$1
+GLOG_vmodule=MemcachedClient=-1 srun --mpi=pmi2 -p $partition \
+    -n8 --gres=gpu:8 --ntasks-per-node=8 \
+    python -u main.py --config $work_path/config.yaml --launcher slurm \
+        --load-iter 70000 \
+        --validate