add badges, fix rerun bug, pruning

README.md

@@ -4,7 +4,7 @@ emoji: 📸🚀🌟
 colorFrom: red
 colorTo: yellow
 sdk: gradio
-sdk_version: 3.36.1
+sdk_version: 3.40.0
 app_file: app.py
 pinned: true
 license: mit

app.py

@@ -31,7 +31,6 @@ import numpy as np
 import plotly.graph_objects as go
 from functools import partial
 
-from lovely_numpy import lo
 import cv2
 from PIL import Image
 import trimesh
@@ -46,16 +45,16 @@ _GPU_INDEX = 0
 
 _TITLE = '''One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization'''
 
+
+# <a style="display:inline-block; margin-left: 1em" href="https://arxiv.org/abs/2306.16928"><img src="https://img.shields.io/badge/arXiv-2306.16928-b31b1b.svg"></a>
 _DESCRIPTION = '''
+<div>
+<a style="display:inline-block" href="http://one-2-3-45.com"><img src="https://img.shields.io/badge/Project_Homepage-f9f7f7?logo=data:image/webp;base64,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"></a>
+<a style="display:inline-block; margin-left: .5em" href="https://arxiv.org/abs/2306.16928"><img src="https://img.shields.io/badge/2306.16928-f9f7f7?logo=data:image/png;base64,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"></a>
+<a style="display:inline-block; margin-left: .5em" href='https://github.com/One-2-3-45/One-2-3-45'><img src='https://img.shields.io/github/stars/One-2-3-45/One-2-3-45?style=social' /></a>
+</div>
 We reconstruct a 3D textured mesh from a single image by initially predicting multi-view images and then lifting them to 3D. 
-[<a href="http://One-2-3-45.com">Project</a>] 
-[<a href="https://github.com/One-2-3-45/One-2-3-45">GitHub</a>] 
 '''
-# _HTML = '''<p>[<a href="https://github.com/One-2-3-45/One-2-3-45">GitHub</a>] 
-# <object alt="GitHub Repo stars" src="https://img.shields.io/github/stars/One-2-3-45/One-2-3-45?style=social&link=https%3A%2F%2Fgithub.com%2FOne-2-3-45%2FOne-2-3-45">
-# </p>'''
-# _HTML = '<script async defer src="https://buttons.github.io/buttons.js"></script> <a class="github-button" href="https://github.com/One-2-3-45/One-2-3-45" data-icon="octicon-star" data-show-count="true" aria-label="Star One-2-3-45/One-2-3-45 on GitHub">Star</a><p>'
-
 _USER_GUIDE = "Please upload an image in the block above (or choose an example above) and click **Run Generation**." 
 _BBOX_1 = "Predicting bounding box for the input image..."
 _BBOX_2 = "Bounding box adjusted. Continue adjusting or **Run Generation**."
@@ -184,11 +183,6 @@ class CameraVisualizer:
             # Extract the new x, y, z coordinates from the rotated coordinates
             x, y, z = rotated_coordinates[..., 0], rotated_coordinates[..., 1], rotated_coordinates[..., 2]
 
-
-            print('x:', lo(x))
-            print('y:', lo(y))
-            print('z:', lo(z))
-
             fig.add_trace(go.Surface(
                 x=x, y=y, z=z,
                 surfacecolor=self._8bit_image,
@@ -316,7 +310,12 @@ def stage1_run(models, device, cam_vis, tmp_dir,
         output_ims = predict_stage1_gradio(model, input_im, save_path=stage1_dir, adjust_set=list(range(4)), device=device, ddim_steps=ddim_steps, scale=scale)
         stage2_steps = 50 # ddim_steps
         zero123_infer(model, tmp_dir, indices=[0], device=device, ddim_steps=stage2_steps, scale=scale)
-        elev_output = estimate_elev(tmp_dir)
+        try:
+            elev_output = estimate_elev(tmp_dir)
+        except:
+            print("Failed to estimate polar angle")
+            elev_output = 90
+        print("Estimated polar angle:", elev_output)
         gen_poses(tmp_dir, elev_output)
         show_in_im1 = np.asarray(input_im, dtype=np.uint8)
         cam_vis.encode_image(show_in_im1, elev=elev_output)
@@ -367,7 +366,7 @@ def stage2_run(models, device, tmp_dir,
     torch.cuda.empty_cache()
     os.chdir(os.path.join(code_dir, 'SparseNeuS_demo_v1/'))
 
-    bash_script = f'CUDA_VISIBLE_DEVICES={_GPU_INDEX} python exp_runner_generic_blender_val.py --specific_dataset_name {dataset} --mode export_mesh --conf confs/one2345_lod0_val_demo.conf  --is_continue'
+    bash_script = f'CUDA_VISIBLE_DEVICES={_GPU_INDEX} python exp_runner_generic_blender_val.py --specific_dataset_name {dataset} --mode export_mesh --conf confs/one2345_lod0_val_demo.conf'
     print(bash_script)
     os.system(bash_script)
     os.chdir(main_dir_path)
@@ -377,13 +376,9 @@ def stage2_run(models, device, tmp_dir,
     mesh_path = os.path.join(tmp_dir, f"mesh{mesh_ext}")
     # Read the textured mesh from .ply file
     mesh = trimesh.load_mesh(ply_path)
-    axis = [1, 0, 0]
-    angle = np.radians(90)
-    rotation_matrix = trimesh.transformations.rotation_matrix(angle, axis)
+    rotation_matrix = trimesh.transformations.rotation_matrix(np.pi/2, [1, 0, 0])
     mesh.apply_transform(rotation_matrix)
-    axis = [0, 0, 1]
-    angle = np.radians(180)
-    rotation_matrix = trimesh.transformations.rotation_matrix(angle, axis)
+    rotation_matrix = trimesh.transformations.rotation_matrix(np.pi, [0, 0, 1])
     mesh.apply_transform(rotation_matrix)
     # flip x
     mesh.vertices[:, 0] = -mesh.vertices[:, 0]
@@ -398,31 +393,16 @@ def stage2_run(models, device, tmp_dir,
     if not is_rerun:
         return (mesh_path)
     else:
-        return (mesh_path, [], gr.update(visible=False), gr.update(visible=False))
+        return (mesh_path, gr.update(value=[]), gr.update(visible=False), gr.update(visible=False))
 
 def nsfw_check(models, raw_im, device='cuda'):
     safety_checker_input = models['clip_fe'](raw_im, return_tensors='pt').to(device)
     (_, has_nsfw_concept) = models['nsfw'](
         images=np.ones((1, 3)), clip_input=safety_checker_input.pixel_values)
-    print('has_nsfw_concept:', has_nsfw_concept)
     del safety_checker_input
     if np.any(has_nsfw_concept):
         print('NSFW content detected.')
-        # Define the image size and background color
-        image_width = image_height = 256
-        background_color = (255, 255, 255)  # White
-        # Create a blank image
-        image = Image.new("RGB", (image_width, image_height), background_color)
-        from PIL import ImageDraw
-        draw = ImageDraw.Draw(image)
-        text = "Potential NSFW content was detected."
-        text_color = (255, 0, 0)
-        text_position = (10, 123)  
-        draw.text(text_position, text, fill=text_color)
-        text = "Please try again with a different image."
-        text_position = (10, 133) 
-        draw.text(text_position, text, fill=text_color)
-        return image
+        return Image.open("unsafe.png")
     else:
         print('Safety check passed.')
         return False
@@ -439,7 +419,7 @@ def preprocess_run(predictor, models, raw_im, preprocess, *bbox_sliders):
 
 def on_coords_slider(image, x_min, y_min, x_max, y_max, color=(88, 191, 131, 255)):
     """Draw a bounding box annotation for an image."""
-    print("on_coords_slider, drawing bbox...")
+    print("Slider adjusted, drawing bbox...")
     image.thumbnail([512, 512], Image.Resampling.LANCZOS)
     image_size = image.size
     if max(image_size) > 224:
@@ -502,15 +482,18 @@ def run_demo(
     examples_full = [os.path.join(example_folder, x) for x in example_fns if x.endswith('.png')]
 
     # Compose demo layout & data flow.
-    css = "#model-3d-out {height: 400px;} #plot-out {height: 450px;}"
-    with gr.Blocks(title=_TITLE, css=css) as demo:
-        gr.Markdown('# ' + _TITLE)
+    with gr.Blocks(title=_TITLE, css="style.css") as demo:
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown('# ' + _TITLE)
+            with gr.Column(scale=0):
+                gr.DuplicateButton(value='Duplicate Space for private use',
+                            elem_id='duplicate-button')
         gr.Markdown(_DESCRIPTION)
-        # gr.HTML(_HTML)
 
         with gr.Row(variant='panel'):
             with gr.Column(scale=1.2):
-                image_block = gr.Image(type='pil', image_mode='RGBA', label='Input image', tool=None).style(height=290)
+                image_block = gr.Image(type='pil', image_mode='RGBA', height=290, label='Input image', tool=None)
 
                 gr.Examples(
                     examples=examples_full,  # NOTE: elements must match inputs list!
@@ -535,7 +518,7 @@ def run_demo(
                 
             with gr.Column(scale=.8):
                 with gr.Row():
-                    bbox_block = gr.Image(type='pil', label="Bounding box", interactive=False).style(height=290)
+                    bbox_block = gr.Image(type='pil', label="Bounding box", height=290, interactive=False)
                     sam_block = gr.Image(type='pil', label="SAM output", interactive=False)
                 max_width = max_height = 256
                 with gr.Row():
@@ -556,20 +539,20 @@ def run_demo(
             with gr.Column(scale=1.15):
                 gr.Markdown('Predicted multi-view images')
                 with gr.Row():
-                    view_1 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_2 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_3 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_4 = gr.Image(interactive=False, show_label=False).style(height=200)
+                    view_1 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_2 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_3 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_4 = gr.Image(interactive=False, height=200, show_label=False)
                 with gr.Row():
                     btn_retry_1 = gr.Checkbox(label='Retry view 1')
                     btn_retry_2 = gr.Checkbox(label='Retry view 2')
                     btn_retry_3 = gr.Checkbox(label='Retry view 3')
                     btn_retry_4 = gr.Checkbox(label='Retry view 4')
                 with gr.Row():
-                    view_5 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_6 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_7 = gr.Image(interactive=False, show_label=False).style(height=200)
-                    view_8 = gr.Image(interactive=False, show_label=False).style(height=200)
+                    view_5 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_6 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_7 = gr.Image(interactive=False, height=200, show_label=False)
+                    view_8 = gr.Image(interactive=False, height=200, show_label=False)
                 with gr.Row():
                     btn_retry_5 = gr.Checkbox(label='Retry view 5')
                     btn_retry_6 = gr.Checkbox(label='Retry view 6')
@@ -663,7 +646,7 @@ def run_demo(
                             ).success(fn=partial(update_guide, _REGEN_2), outputs=[guide_text], queue=False)
 
 
-    demo.launch(enable_queue=True, share=False, max_threads=80) # auth=("admin", os.environ['PASSWD'])
+    demo.queue().launch(share=False, max_threads=80) # auth=("admin", os.environ['PASSWD'])
 
 
 if __name__ == '__main__':

pre-requirements.txt

@@ -1,5 +1,5 @@
-# --extra-index-url https://download.pytorch.org/whl/cu113
-torch>=1.12.1
+--extra-index-url https://download.pytorch.org/whl/cu118
+torch>=2.0.0
 torchvision>=0.13.1
 albumentations>=0.4.3
 opencv-python>=4.5.5.64
@@ -22,8 +22,6 @@ diffusers>=0.12.1
 datasets[vision]>=2.4.0
 carvekit-colab>=4.1.0
 rich>=13.3.2
-lovely-numpy>=0.2.8
-lovely-tensors>=0.1.14
 plotly>=5.13.1
 -e git+https://github.com/CompVis/taming-transformers.git#egg=taming-transformers
 # elev est
@@ -32,7 +30,6 @@ easydict
 glumpy
 gym
 h5py
-imageio
 loguru
 matplotlib
 # mplib
@@ -55,18 +52,14 @@ tqdm
 transforms3d
 trimesh
 yacs
-zarr
-sapien
+# zarr
+# sapien
 pyglet==1.5.27
-wis3d
+# wis3d
 gdown
 git+https://github.com/NVlabs/nvdiffrast.git
-# shap-e
-git+https://github.com/openai/shap-e@8625e7c
+git+https://github.com/openai/CLIP.git
 # segment anything
-opencv-python
-pycocotools 
-matplotlib 
 onnxruntime 
 onnx
 git+https://github.com/facebookresearch/segment-anything.git

requirements.txt

@@ -1,12 +1,7 @@
 # sparseneus
 # -e git+https://github.com/mit-han-lab/[email protected]#egg=torchsparse
-opencv_python
-trimesh
 numpy
 pyhocon
 icecream
-tqdm
-scipy
 PyMCubes
-ninja
-# sudo apt-get install libsparsehash-dev
+ninja

style.css

@@ -0,0 +1,13 @@
+#model-3d-out {
+    height: 400px;
+} 
+
+#plot-out {
+    height: 450px;
+}
+
+#duplicate-button {
+    margin-left: auto;
+    color: #fff;
+    background: #1565c0;
+  }