LutaoJiang commited on
Commit
40ae5e2
·
1 Parent(s): cdd5e3e
Files changed (1) hide show
  1. app.py +9 -8
app.py CHANGED
@@ -187,7 +187,7 @@ else:
187
  # print(f"Before text_to_detailed: {torch.cuda.memory_allocated() / 1024**3} GB")
188
  return k3d_wrapper.get_detailed_prompt(prompt, seed)
189
 
190
- @spaces.GPU(duration=120)
191
  def text_to_image(prompt, seed=None, strength=1.0,lora_scale=1.0, num_inference_steps=18, redux_hparam=None, init_image=None, **kwargs):
192
  # subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
193
  # print(f"Before text_to_image: {torch.cuda.memory_allocated() / 1024**3} GB")
@@ -210,7 +210,7 @@ else:
210
  **kwargs)
211
  return result[-1]
212
 
213
- @spaces.GPU(duration=120)
214
  def image2mesh_preprocess_(input_image_, seed, use_mv_rgb=True):
215
  global preprocessed_input_image
216
 
@@ -225,7 +225,7 @@ else:
225
  return reference_save_path, caption
226
 
227
 
228
- @spaces.GPU(duration=120)
229
  def image2mesh_main_(reference_3d_bundle_image, caption, seed, strength1=0.5, strength2=0.95, enable_redux=True, use_controlnet=True, if_video=True):
230
  subprocess.run(['nvidia-smi'])
231
  global mesh_cache
@@ -252,7 +252,7 @@ else:
252
  return gen_save_path, recon_mesh_path, mesh_cache
253
  # return gen_save_path, recon_mesh_path
254
 
255
- @spaces.GPU(duration=120)
256
  def bundle_image_to_mesh(
257
  gen_3d_bundle_image,
258
  camera_radius=3.5,
@@ -429,10 +429,11 @@ with gr.Blocks(css="""
429
  # Modify the Examples section to display horizontally
430
  gr.Examples(
431
  examples=[
432
- ["A dog wearing a hat"],
 
433
  ["A battle mech in a mix of red, blue, and black color, with a cannon on the head."],
434
  ["骷髅头, 邪恶的"],
435
- ["A person wearing a virtual reality headset, sitting position, bent legs, clasped hands."],
436
  ],
437
  inputs=[prompt],
438
  label="Example Prompts",
@@ -440,7 +441,7 @@ with gr.Blocks(css="""
440
  )
441
 
442
  with gr.Accordion("Advanced Parameters", open=False):
443
- seed1 = gr.Number(value=10, label="Seed")
444
 
445
  btn_one_click_generate = gr.Button("One-click Generation", elem_id="one-click-generate-btn", elem_classes=["orange-button"])
446
 
@@ -452,7 +453,7 @@ with gr.Blocks(css="""
452
 
453
  with gr.Accordion("Advanced Parameters", open=False):
454
  with gr.Row():
455
- img_gen_seed = gr.Number(value=10, label="Image Generation Seed")
456
  num_inference_steps = gr.Slider(minimum=1, maximum=50, value=18, step=1, label="Inference Steps")
457
  with gr.Row():
458
  strength = gr.Slider(minimum=0.0, maximum=1.0, value=1.0, step=0.05, label="Strength")
 
187
  # print(f"Before text_to_detailed: {torch.cuda.memory_allocated() / 1024**3} GB")
188
  return k3d_wrapper.get_detailed_prompt(prompt, seed)
189
 
190
+ @spaces.GPU
191
  def text_to_image(prompt, seed=None, strength=1.0,lora_scale=1.0, num_inference_steps=18, redux_hparam=None, init_image=None, **kwargs):
192
  # subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
193
  # print(f"Before text_to_image: {torch.cuda.memory_allocated() / 1024**3} GB")
 
210
  **kwargs)
211
  return result[-1]
212
 
213
+ @spaces.GPU
214
  def image2mesh_preprocess_(input_image_, seed, use_mv_rgb=True):
215
  global preprocessed_input_image
216
 
 
225
  return reference_save_path, caption
226
 
227
 
228
+ @spaces.GPU
229
  def image2mesh_main_(reference_3d_bundle_image, caption, seed, strength1=0.5, strength2=0.95, enable_redux=True, use_controlnet=True, if_video=True):
230
  subprocess.run(['nvidia-smi'])
231
  global mesh_cache
 
252
  return gen_save_path, recon_mesh_path, mesh_cache
253
  # return gen_save_path, recon_mesh_path
254
 
255
+ @spaces.GPU
256
  def bundle_image_to_mesh(
257
  gen_3d_bundle_image,
258
  camera_radius=3.5,
 
429
  # Modify the Examples section to display horizontally
430
  gr.Examples(
431
  examples=[
432
+ ["A cat"],
433
+ ["A person wearing a virtual reality headset, sitting position, bent legs, clasped hands."],
434
  ["A battle mech in a mix of red, blue, and black color, with a cannon on the head."],
435
  ["骷髅头, 邪恶的"],
436
+
437
  ],
438
  inputs=[prompt],
439
  label="Example Prompts",
 
441
  )
442
 
443
  with gr.Accordion("Advanced Parameters", open=False):
444
+ seed1 = gr.Number(value=666, label="Seed")
445
 
446
  btn_one_click_generate = gr.Button("One-click Generation", elem_id="one-click-generate-btn", elem_classes=["orange-button"])
447
 
 
453
 
454
  with gr.Accordion("Advanced Parameters", open=False):
455
  with gr.Row():
456
+ img_gen_seed = gr.Number(value=666, label="Image Generation Seed")
457
  num_inference_steps = gr.Slider(minimum=1, maximum=50, value=18, step=1, label="Inference Steps")
458
  with gr.Row():
459
  strength = gr.Slider(minimum=0.0, maximum=1.0, value=1.0, step=0.05, label="Strength")