Views
No views yet
input_mode=compressed_224
Use the participant-kit public image size. OOI and planner internally upscale to 480, while the VLA keeps the original 224 camera images and uses a 224 resize of the OOI crop.input_mode=native_480
Local-only mode for native 480x480 camera inputs. The public competition contract still uses 224x224, so this is mainly for controlled internal runs.pipeline_mode=end_to_end
Single process with PyTorch OOI/planner plus JAX OpenPI on one GPU.pipeline_mode=separate_servers
Single public Zenoh server, but two internal worker processes:1cd E:\Robot-Origami-Challenge\RO-Inference
2python .\serve_origami_policy.py `
3 --config .\configs\origami_inference.yaml `
4 --endpoint tcp/127.0.0.1:7447 `
5 --session-id test-session `
6 --input-mode compressed_224 `
7 --pipeline-mode end_to_end `
8 --speed 1.0 `
9 --num-sampled-actions 20 `
10 --policy-sample-steps 10 `
11 --planner-transition-threshold 0.751cd E:\Robot-Origami-Challenge\RO-Inference
2python .\scripts\verify_submission_bundle.py --config .\configs\origami_inference.yamldinov3-vits16plus-pretrain-lvd1689mpaligemma_tokenizer.modelnorm_stats.jsonorigami_tactile_norm_stats.jsonRO-InferenceRO-Inference directory as the Docker context:1cd E:\Robot-Origami-Challenge\RO-Inference
2docker build -f .\docker\submission-zenoh-bundled.Dockerfile -t ro-inference-submission .ORIGAMI_ZENOH_ENDPOINTORIGAMI_SESSION_IDORIGAMI_SPEEDORIGAMI_NUM_SAMPLED_ACTIONSORIGAMI_PLANNER_TRANSITION_THRESHOLDORIGAMI_POLICY_SAMPLE_STEPSORIGAMI_INPUT_MODEORIGAMI_PIPELINE_MODEcompressed_224. native_480 remains available as a local debug mode.