From eb4cdbe58281481d77067b4becfab9a7042d73c0 Mon Sep 17 00:00:00 2001 From: Lorenzo Date: Wed, 6 Jan 2021 15:29:59 +0100 Subject: [PATCH] add description --- docs/MonoLoco++.md | 28 +++++++++++++++++++++------- 1 file changed, 21 insertions(+), 7 deletions(-) diff --git a/docs/MonoLoco++.md b/docs/MonoLoco++.md index 41ac517..5d2770d 100644 --- a/docs/MonoLoco++.md +++ b/docs/MonoLoco++.md @@ -19,7 +19,7 @@ Our vision-based system (i) is privacy-safe, (ii) works with any fixed or moving This readme is in Beta version and refers to the `update` branch. It is currently under development. ## Predictions -For a quick setup download a pifpaf and a MonoLoco++ models from here and save them into `data/models`. +For a quick setup download a pifpaf and a MonoLoco++ models from TODO and save them into `data/models`. ### 3D Localization The predict script receives an image (or an entire folder using glob expressions), @@ -28,20 +28,34 @@ and runs Monoloco++ for 3d location of the detected poses. The command `--net` defines if saving pifpaf outputs, MonoLoco++ outputs or MonStereo ones. You can check all commands for Pifpaf at [openpifpaf](https://github.com/vita-epfl/openpifpaf). - Output options include json files and/or visualization of the predictions on the image in *frontal mode*, *birds-eye-view mode* or *combined mode* and can be specified with `--output_types` -Below an example image and comparison with ground-truth. -Ground-truth KITTI files for comparing results can be downloaded from here and should be saved into `data/arrays` -Ground-truth files can also be generated, more info in the preprocessing section +Ground-truth KITTI files for comparing results can be downloaded from +[here](https://drive.google.com/drive/folders/1jZToVMBEZQMdLB5BAIq2CdCLP5kzNo9t?usp=sharing) +(file called *names-kitti*) and should be saved into `data/arrays` +Ground-truth files can also be generated, more info in the preprocessing section. + +For an example image, run the following command: + ``` -python -m monstereo.run predict --net monoloco_pp --glob docs/002282.png --output_types multi ---model data/models/monoloco_pp-201203-1424.pkl -o --long-edge 2500 --n_dropout 50 +python -m monstereo.run predict \ +docs/002282.png \ +--net monoloco_pp \ +--output_types multi \ +--model data/models/monoloco_pp-201203-1424.pkl \ +--path_gt data/arrays/names-kitti-200615-1022.json \ +-o \ +--long-edge +--n_dropout <50 to include epistemic uncertainty, 0 otherwise> ``` +![predict_ground_truth](docs/out_002282.png.multi.jpg) + To show all the instances estimated by MonoLoco add the argument `show_all` to the above command. +![predict_all](docs/out_002282.png.multi_all.jpg) + ### Social Distancing WIP