测试

app.py

@@ -2,60 +2,37 @@ import logging
 import os
 import tempfile
 import time
-
 import gradio as gr
 import numpy as np
 import rembg
 import torch
 from PIL import Image
 from functools import partial
-
 from tsr.system import TSR
 from tsr.utils import remove_background, resize_foreground, to_gradio_3d_orientation
-
-#HF_TOKEN = os.getenv("HF_TOKEN")
-
-HEADER = """
-**TripoSR** is a state-of-the-art open-source model for **fast** feedforward 3D reconstruction from a single image, developed in collaboration between [Tripo AI](https://www.tripo3d.ai/) and [Stability AI](https://stability.ai/).
-**Tips:**
-1. If you find the result is unsatisfied, please try to change the foreground ratio. It might improve the results.
-2. Please disable "Remove Background" option only if your input image is RGBA with transparent background, image contents are centered and occupy more than 70% of image width or height.
-"""
-
-
+import argparse
 if torch.cuda.is_available():
     device = "cuda:0"
 else:
     device = "cpu"
-
-d = os.environ.get("DEVICE", None)
-if d != None:
-    device = d 
-
 model = TSR.from_pretrained(
     "stabilityai/TripoSR",
     config_name="config.yaml",
     weight_name="model.ckpt",
-#    token=HF_TOKEN
 )
-model.renderer.set_chunk_size(131072)
+# adjust the chunk size to balance between speed and memory usage
+model.renderer.set_chunk_size(8192)
 model.to(device)
-
 rembg_session = rembg.new_session()
-
-
 def check_input_image(input_image):
     if input_image is None:
         raise gr.Error("No image uploaded!")
-
-
 def preprocess(input_image, do_remove_background, foreground_ratio):
     def fill_background(image):
         image = np.array(image).astype(np.float32) / 255.0
         image = image[:, :, :3] * image[:, :, 3:4] + (1 - image[:, :, 3:4]) * 0.5
         image = Image.fromarray((image * 255.0).astype(np.uint8))
         return image
-
     if do_remove_background:
         image = input_image.convert("RGB")
         image = remove_background(image, rembg_session)
@@ -66,25 +43,26 @@ def preprocess(input_image, do_remove_background, foreground_ratio):
         if image.mode == "RGBA":
             image = fill_background(image)
     return image
-
-
-def generate(image):
+def generate(image, mc_resolution, formats=["obj", "glb"]):
     scene_codes = model(image, device=device)
-    mesh = model.extract_mesh(scene_codes)[0]
+    mesh = model.extract_mesh(scene_codes, resolution=mc_resolution)[0]
     mesh = to_gradio_3d_orientation(mesh)
-    mesh_path = tempfile.NamedTemporaryFile(suffix=".obj", delete=False)
-    mesh_path2 = tempfile.NamedTemporaryFile(suffix=".glb", delete=False)
-    mesh.export(mesh_path.name)
-    mesh.export(mesh_path2.name)
-    return mesh_path.name, mesh_path2.name
-
+    rv = []
+    for format in formats:
+        mesh_path = tempfile.NamedTemporaryFile(suffix=f".{format}", delete=False)
+        mesh.export(mesh_path.name)
+        rv.append(mesh_path.name)
+    return rv
 def run_example(image_pil):
     preprocessed = preprocess(image_pil, False, 0.9)
-    mesh_name, mesn_name2 = generate(preprocessed)
-    return preprocessed, mesh_name, mesh_name2
-
-with gr.Blocks() as demo:
-    gr.Markdown(HEADER)
+    mesh_name_obj, mesh_name_glb = generate(preprocessed, 256, ["obj", "glb"])
+    return preprocessed, mesh_name_obj, mesh_name_glb
+with gr.Blocks(title="TripoSR") as demo:
+    gr.Markdown(
+        """
+        图像生成3d模型
+        """
+    )
     with gr.Row(variant="panel"):
         with gr.Column():
             with gr.Row():
@@ -108,30 +86,52 @@ with gr.Blocks() as demo:
                         value=0.85,
                         step=0.05,
                     )
+                    mc_resolution = gr.Slider(
+                        label="Marching Cubes Resolution",
+                        minimum=32,
+                        maximum=320,
+                        maximum=1024,
+                        value=256,
+                        step=32
+                    )
             with gr.Row():
                 submit = gr.Button("Generate", elem_id="generate", variant="primary")
         with gr.Column():
-            with gr.Tab("obj"):
-                output_model = gr.Model3D(
-                    label="Output Model",
+            with gr.Tab("OBJ"):
+                output_model_obj = gr.Model3D(
+                    label="Output Model (OBJ Format)",
                     interactive=False,
                 )
-            with gr.Tab("glb"):
-                output_model2 = gr.Model3D(
-                    label="Output Model",
+                gr.Markdown("Note: The model shown here is flipped. Download to get correct results.")
+            with gr.Tab("GLB"):
+                output_model_glb = gr.Model3D(
+                    label="Output Model (GLB Format)",
                     interactive=False,
                 )
+                gr.Markdown("Note: The model shown here has a darker appearance. Download to get correct results.")
     with gr.Row(variant="panel"):
         gr.Examples(
             examples=[
-                os.path.join("examples", img_name) for img_name in sorted(os.listdir("examples"))
+                "examples/hamburger.png",
+                "examples/poly_fox.png",
+                "examples/robot.png",
+                "examples/teapot.png",
+                "examples/tiger_girl.png",
+                "examples/horse.png",
+                "examples/flamingo.png",
+                "examples/unicorn.png",
+                "examples/chair.png",
+                "examples/iso_house.png",
+                "examples/marble.png",
+                "examples/police_woman.png",
+                "examples/captured.jpeg",
             ],
             inputs=[input_image],
-            outputs=[processed_image, output_model, output_model2],
-            #cache_examples=True,
+            outputs=[processed_image, output_model_obj, output_model_glb],
+            cache_examples=False,
             fn=partial(run_example),
             label="Examples",
-            examples_per_page=20
+            examples_per_page=20,
         )
     submit.click(fn=check_input_image, inputs=[input_image]).success(
         fn=preprocess,
@@ -139,9 +139,8 @@ with gr.Blocks() as demo:
         outputs=[processed_image],
     ).success(
         fn=generate,
-        inputs=[processed_image],
-        outputs=[output_model, output_model2],
+        inputs=[processed_image, mc_resolution],
+        outputs=[output_model_obj, output_model_glb],
     )
-
 demo.queue(max_size=10)
 demo.launch()