diff --git a/README.md b/README.md index 283e904..f47498c 100644 --- a/README.md +++ b/README.md @@ -5,14 +5,14 @@ This repository contains the code for two research projects: 1. **MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization** [README](https://github.com/vita-epfl/monstereo/tree/master/docs/MonStereo.md) & [Article](https://arxiv.org/abs/2008.10913) - ![monstereo 1](docs/000840_multi.png) + ![monstereo 1](docs/000840_multi.jpg) 2. **Perceiving Humans: from Monocular 3D Localization to Social Distancing (MonoLoco++)** [README](https://github.com/vita-epfl/monstereo/tree/master/docs/MonoLoco_pp.md) & [Article](https://arxiv.org/abs/2009.00984) - ![social distancing](docs/pull_sd.png) + ![social distancing](docs/social_distancing.jpg) - ![monoloco_pp](docs/truck.png) + ![monoloco_pp](docs/truck.jpg) Both projects has been built upon the CVPR'19 project [Openpifpaf](https://github.com/vita-epfl/openpifpaf) for 2D pose estimation and the ICCV'19 project [MonoLoco](https://github.com/vita-epfl/monoloco) for monocular 3D localization. diff --git a/docs/000840_multi.png b/docs/000840_multi.png deleted file mode 100644 index d81ceaa..0000000 Binary files a/docs/000840_multi.png and /dev/null differ diff --git a/docs/MonStereo.md b/docs/MonStereo.md index f8525da..5e74893 100644 --- a/docs/MonStereo.md +++ b/docs/MonStereo.md @@ -66,13 +66,13 @@ After downloading model and ground-truth file, a demo can be tested with the fol --model data/models/ms-200710-1511.pkl --z_max 30 --checkpoint resnet152 --path_gt data/arrays/names-kitti-200615-1022.json -o data/output` -![Crowded scene](out_000840.png) +![Crowded scene](out_000840.jpg) `python3 -m monstereo.run predict --glob docs/005523*.png --output_types multi --scale 2 --model data/models/ms-200710-1511.pkl --z_max 30 --checkpoint resnet152 --path_gt data/arrays/names-kitti-200615-1022.json -o data/output` -![Occluded hard example](out_005523.png) +![Occluded hard example](out_005523.jpg) # Preprocessing Preprocessing and training step are already fully supported by the code provided, diff --git a/docs/out_000840.png b/docs/out_000840.png deleted file mode 100644 index 77eefa7..0000000 Binary files a/docs/out_000840.png and /dev/null differ diff --git a/docs/out_005523.png b/docs/out_005523.png deleted file mode 100644 index 9299ef9..0000000 Binary files a/docs/out_005523.png and /dev/null differ diff --git a/docs/pull_sd.png b/docs/pull_sd.png deleted file mode 100644 index 8cc8301..0000000 Binary files a/docs/pull_sd.png and /dev/null differ diff --git a/docs/truck.png b/docs/truck.png deleted file mode 100644 index f77d8e2..0000000 Binary files a/docs/truck.png and /dev/null differ diff --git a/monstereo/visuals/figures.py b/monstereo/visuals/figures.py index 81f4d73..226625b 100644 --- a/monstereo/visuals/figures.py +++ b/monstereo/visuals/figures.py @@ -28,7 +28,7 @@ def show_results(dic_stats, clusters, net, dir_fig, show=False, save=False): x_max = 31 y_min = 0 # y_max = 2.2 - y_max = 3.5 if net == 'monstereo' else 2.6 + y_max = 3.5 if net == 'monstereo' else 2.7 xx = np.linspace(x_min, x_max, 100) excl_clusters = ['all', 'easy', 'moderate', 'hard', '49'] clusters = [clst for clst in clusters if clst not in excl_clusters] @@ -76,10 +76,10 @@ def show_spread(dic_stats, clusters, net, dir_fig, show=False, save=False): assert net in ('monoloco_pp', 'monstereo'), "network not recognized" phase = 'test' - excl_clusters = ['all', 'easy', 'moderate', 'hard'] + excl_clusters = ['all', 'easy', 'moderate', 'hard', '49'] clusters = [clst for clst in clusters if clst not in excl_clusters] x_min = 3 - x_max = 42 + x_max = 31 y_min = 0 plt.figure(2, figsize=FIGSIZE) @@ -87,10 +87,10 @@ def show_spread(dic_stats, clusters, net, dir_fig, show=False, save=False): bbs = np.array([dic_stats[phase][net][key]['std_ale'] for key in clusters[:-1]]) xx = np.linspace(x_min, x_max, 100) if net == 'monoloco_pp': - y_max = 5 + y_max = 2.7 color = 'deepskyblue' epis = np.array([dic_stats[phase][net][key]['std_epi'] for key in clusters[:-1]]) - plt.plot(xxs, epis, marker='o', color='coral', label="Combined uncertainty (\u03C3)") + plt.plot(xxs, epis, marker='o', color='coral', linewidth=4, markersize=8, label="Combined uncertainty (\u03C3)") else: y_max = 3.5 color = 'b'