i

apps/third_party/CRM/imagedream/ldm/modules/attention.py

@@ -166,7 +166,7 @@ class MemoryEfficientCrossAttention(nn.Module):
         self.to_out = nn.Sequential(
             nn.Linear(inner_dim, query_dim), nn.Dropout(dropout)
         )
-        self.attention_op: Optional[Any] = None
+        self.attention_op = None
 
     def forward(self, x, context=None, mask=None):
         q = self.to_q(x)

apps/third_party/CRM/imagedream/ldm/modules/diffusionmodules/model.py

@@ -217,7 +217,7 @@ class MemoryEfficientAttnBlock(nn.Module):
         self.proj_out = torch.nn.Conv2d(
             in_channels, in_channels, kernel_size=1, stride=1, padding=0
         )
-        self.attention_op: Optional[Any] = None
+        self.attention_op = None
 
     def forward(self, x):
         h_ = x

gradio_app.py

@@ -38,7 +38,7 @@ By mimicking the artist/craftsman modeling workflow, we propose CraftsMan (aka
 then a multi-view normal enhanced image generation model is used to refine the mesh.
 We provide the coarse 3D diffusion part here. 
 <br>
-If you found Crafts is helpful, please help to ⭐ the <a href='https://github.com/wyysf-98/CraftsMan/' target='_blank'>Github Repo</a>. Thanks!
+If you found CraftsMan is helpful, please help to ⭐ the <a href='https://github.com/wyysf-98/CraftsMan/' target='_blank'>Github Repo</a>. Thanks!
 <a style="display:inline-block; margin-left: .5em" href='https://github.com/wyysf-98/CraftsMan/'><img src='https://img.shields.io/github/stars/wyysf-98/CraftsMan?style=social' /></a>
 <br>
 *please note that the model is fliped due to the gradio viewer, please download the obj file and you will get the correct mesh.
@@ -81,6 +81,8 @@ def gen_mvimg(
     mvimg_model, text, image, crop_size, seed, guidance_scale, step
 ):
     global crm_pipeline
+    if seed == 0:
+        seed = np.random.randint(1, 65535)
     crm_pipeline.set_seed(seed)
     rt_dict = crm_pipeline(image, scale=guidance_scale, step=step)
     mv_imgs = rt_dict["stage1_images"]
@@ -206,7 +208,7 @@ if __name__=="__main__":
                 with gr.Row():
                     gr.Markdown('''Try a different <b>seed</b> if the result is unsatisfying. Good Luck :)''')
                 with gr.Row():
-                    seed = gr.Number(42, label='Seed', show_label=True)
+                    seed = gr.Number(0, label='Seed', show_label=True)
                     more = gr.CheckboxGroup(["Remesh", "Symmetry(TBD)"], label="More", show_label=False)
                     # remesh = gr.Checkbox(value=False, label='Remesh')
                     # symmetry = gr.Checkbox(value=False, label='Symmetry(TBD)', interactive=False)
@@ -256,15 +258,16 @@ if __name__=="__main__":
                         background_choice = gr.Dropdown(label="Backgroud Choice", value="Auto Remove Background",choices=list(background_choice.keys()))
                         rmbg_type = gr.Dropdown(label="Backgroud Remove Type", value="rembg",choices=['sam', "rembg"])
                         backgroud_color = gr.ColorPicker(label="Background Color", value="#FFFFFF", interactive=True)
+                        # backgroud_color = gr.ColorPicker(label="Background Color", value="#7F7F7F", interactive=True)
                         
                     with gr.Row():
                         mvimg_guidance_scale = gr.Number(value=3.5, minimum=3, maximum=10, label="2D Guidance Scale")
-                        mvimg_steps = gr.Number(value=30, minimum=20, maximum=100, label="2D Sample Steps", precision=0)
+                        mvimg_steps = gr.Number(value=30, minimum=20, maximum=100, label="2D Sample Steps")
             
                 with gr.Accordion('Advanced options (3D)', open=False):
                     with gr.Row():
                         guidance_scale = gr.Number(label="3D Guidance Scale", value=7.5, minimum=3.0, maximum=10.0)
-                        steps = gr.Number(value=50, minimum=20, maximum=100, label="3D Sample Steps", precision=0)
+                        steps = gr.Number(value=50, minimum=20, maximum=100, label="3D Sample Steps")
                         
                     with gr.Row():
                         scheduler = gr.Dropdown(label="scheluder", value="DDIMScheduler",choices=list(scheluder_dict.keys()))