Spaces:
Running
on
T4
Running
on
T4
Update gradio_app.py
Browse files- gradio_app.py +4 -5
gradio_app.py
CHANGED
@@ -79,14 +79,14 @@ def run_inference(args, cfg, model, batch):
|
|
79 |
images = batch["image"].to(device)
|
80 |
crop_parameters = batch["crop_parameters"].to(device)
|
81 |
|
82 |
-
|
83 |
model=model,
|
84 |
images=images,
|
85 |
device=device,
|
86 |
crop_parameters=crop_parameters,
|
|
|
87 |
num_patches_x=cfg.training.full_num_patches_x,
|
88 |
num_patches_y=cfg.training.full_num_patches_y,
|
89 |
-
additional_timesteps=list(range(11)),
|
90 |
calculate_intrinsics=True,
|
91 |
max_num_images=8,
|
92 |
mode="segment",
|
@@ -94,7 +94,6 @@ def run_inference(args, cfg, model, batch):
|
|
94 |
use_homogeneous=True,
|
95 |
seed=0,
|
96 |
)
|
97 |
-
pred_cameras, pred_rays = additional_cams[10]
|
98 |
|
99 |
# Unnormalize and resize input images
|
100 |
images = unnormalize_image(images, return_numpy=False, return_int=False)
|
@@ -142,7 +141,7 @@ if __name__ == "__main__":
|
|
142 |
_DESCRIPTION = """
|
143 |
<div>
|
144 |
<a style="display:inline-block" href="https://qitaozhao.github.io/DiffusionSfM"><img src='https://img.shields.io/badge/public_website-8A2BE2'></a>
|
145 |
-
<a style="display:inline-block; margin-left: .5em" href='https://github.com/QitaoZhao/
|
146 |
</div>
|
147 |
DiffusionSfM learns to predict scene geometry and camera poses as pixel-wise ray origins and endpoints using a denoising diffusion model.
|
148 |
"""
|
@@ -205,7 +204,7 @@ if __name__ == "__main__":
|
|
205 |
height=520,
|
206 |
zoom_speed=0.5,
|
207 |
pan_speed=0.5,
|
208 |
-
label="3D Point
|
209 |
)
|
210 |
|
211 |
# Link image gallery selection
|
|
|
79 |
images = batch["image"].to(device)
|
80 |
crop_parameters = batch["crop_parameters"].to(device)
|
81 |
|
82 |
+
(pred_cameras, pred_rays), _ = predict_cameras(
|
83 |
model=model,
|
84 |
images=images,
|
85 |
device=device,
|
86 |
crop_parameters=crop_parameters,
|
87 |
+
stop_iteration=90,
|
88 |
num_patches_x=cfg.training.full_num_patches_x,
|
89 |
num_patches_y=cfg.training.full_num_patches_y,
|
|
|
90 |
calculate_intrinsics=True,
|
91 |
max_num_images=8,
|
92 |
mode="segment",
|
|
|
94 |
use_homogeneous=True,
|
95 |
seed=0,
|
96 |
)
|
|
|
97 |
|
98 |
# Unnormalize and resize input images
|
99 |
images = unnormalize_image(images, return_numpy=False, return_int=False)
|
|
|
141 |
_DESCRIPTION = """
|
142 |
<div>
|
143 |
<a style="display:inline-block" href="https://qitaozhao.github.io/DiffusionSfM"><img src='https://img.shields.io/badge/public_website-8A2BE2'></a>
|
144 |
+
<a style="display:inline-block; margin-left: .5em" href='https://github.com/QitaoZhao/DiffusionSfM'><img src='https://img.shields.io/github/stars/QitaoZhao/DiffusionSfM?style=social'/></a>
|
145 |
</div>
|
146 |
DiffusionSfM learns to predict scene geometry and camera poses as pixel-wise ray origins and endpoints using a denoising diffusion model.
|
147 |
"""
|
|
|
204 |
height=520,
|
205 |
zoom_speed=0.5,
|
206 |
pan_speed=0.5,
|
207 |
+
label="3D Point Clouds and Recovered Cameras"
|
208 |
)
|
209 |
|
210 |
# Link image gallery selection
|