feat: base pipeline

main.py

+from gradio_client import Client, handle_file
+
+client = Client("JeffreyXiang/TRELLIS")
+
+preprocessed_image = client.predict(
+  image=handle_file('https://i.pinimg.com/564x/79/b3/6d/79b36deeb891cf65e41c743f5350d6cf.jpg'),
+  api_name="/preprocess_image"
+)
+
+rand_seed = client.predict(
+  randomize_seed=True,
+  seed=0,
+  api_name="/get_seed"
+)
+
+result = client.predict(
+  image=handle_file(preprocessed_image),
+  multiimages=[],
+  seed=rand_seed,
+  ss_guidance_strength=rand_seed,
+  ss_sampling_steps=7.5,
+  slat_guidance_strength=12,
+  slat_sampling_steps=3,
+  multiimage_algo="12",
+  api_name="/image_to_3d"
+)
+
+print(result)
+
+print("image_to_3d ok")
+
+client.predict(
+  api_name="/lambda_2"
+)
+
+client.predict(
+  mesh_simplify=None,
+  texture_size=0.95,
+  api_name="/extract_glb"
+)
+
+client.predict(
+  api_name="/lambda_4"
+)

requirements.txt

+gradio_client>=1.7.0