remove unnacessary comments

app.py

@@ -6,22 +6,7 @@ from diffusers import  KDPM2DiscreteScheduler,KDPM2AncestralDiscreteScheduler,PN
 from diffusers import DPMSolverMultistepScheduler
 import random
 
-# pipe = StableDiffusionPipeline.from_pretrained(
-#     "SG161222/Realistic_Vision_V5.1_noVAE",
-#     torch_dtype=torch.float16,
-#     use_safetensors=True,
-# ).to("cpu")
-
-
-
-
 def set_pipeline(model_id_repo,scheduler):
-#     pipe = StableDiffusionPipeline.from_single_file(
-#         "/home/ubuntu/stable-diffusion-webui/models/Stable-diffusion/realisticVisionV51_v51VAE.safetensors",
-#         # torch_dtype=torch.float16,
-#         use_safetensors=True,
-#     ).to("cpu")
-
 
     model_ids_dict = {
     "dreamshaper": "Lykon/DreamShaper",
@@ -34,12 +19,6 @@ def set_pipeline(model_id_repo,scheduler):
     print("model_repo :",model_repo)
 
 
-    # pipe = StableDiffusionPipeline.from_pretrained(
-    #     model_repo,
-    #     # torch_dtype=torch.float16,                               # to run on cpu
-    #     use_safetensors=True,
-    # ).to("cpu")
-
     pipe = StableDiffusionPipeline.from_pretrained(
         model_repo,
         # torch_dtype=torch.float16,                               # to run on cpu
@@ -68,10 +47,6 @@ def set_pipeline(model_id_repo,scheduler):
     else:
         pass  
 
-    # # prompt = "a photo of an astronaut riding a horse on mars"
-    # # pipe.enable_attention_slicing()
-    # image = pipe(prompt).images[0]
-    # image.save("1.png")
     return pipe
 
 
@@ -88,10 +63,6 @@ def img_args(
              seed = 0
              ):
 
-    print(model_id_repo)
-    print(scheduler)
-    print(prompt,"&&&&&&&&&&&&&&&&")
-
     pipe = set_pipeline(model_id_repo,scheduler)
 
     if seed == 0:
@@ -111,8 +82,6 @@ def img_args(
                  num_images_per_prompt = num_images_per_prompt, # default 1
                  generator = generator,                
                  ).images
-    print(image,"#############")
-    # image.save("1.png")
     return image
 
 
@@ -145,62 +114,3 @@ with block as image_gen:
     run_btn.click(fn=img_args,inputs=[prompt,negative_prompt,model_selection,schduler_selection,height_slider,width_slider,num_inference_steps_slider,guidance_scale_slider,num_images_per_prompt_slider,seed_slider],outputs=[out_img])            
 image_gen.launch()
 
-# block = gr.Blocks().queue()
-# block.title = "Inpaint Anything"
-# with block as inpaint_anything_interface:
-#     with gr.Column():
-#         with gr.Row():
-#             gr.Markdown("## Inpainting with Segment Anything (Multi Controlnet)")
-#         with gr.Row():
-#             with gr.Column():
-#                 # with gr.Row():
-#                 model_selection = gr.Dropdown(choices=["dreamshaper","deliberate","realisticVisionV51_v51VAE","revAnimated_v121Inp","runwayml","Realistic_Vision_V5_1_noVAE"],value = "Realistic_Vision_V5_1_noVAE",label="Models")
-#                 # scheduler = gr.Dropdown(choices=["DDIM","Euler","Euler a","UniPC","DPM2 Karras","DPM2 a Karras","PNDM","DPM++ 2M Karras","DPM++ 2M SDE Karras"],value = "Euler a",label="Sampler")
-#                 input_image = gr.Image(type="numpy",label="input",height=400)
-#                 run_btn = gr.Button("Run Segment", elem_id="select_btn", variant="primary")
-
-#                 prompt = gr.Textbox(placeholder="what you want to generate")
-#                 guidance_scale_slider = gr.Slider(label="Guidance Scale", minimum=0, maximum=20.0, value=7.5, step=0.5)
-#                 inference_slider = gr.Slider(label="Guidance Scale", minimum=0, maximum=150, value=50, step=1)
-#                 with gr.Row():
-#                     canny_slider = gr.Slider(label="Canny Slider", minimum=0, maximum=1.0, value=0.5, step=0.1)
-#                     depth_slider = gr.Slider(label="Depth Slider", minimum=0, maximum=1.0, value=0.5, step=0.1)
-#                     seg_slider = gr.Slider(label="Segment Slider", minimum=0, maximum=1.0, value=0.5, step=0.1)
-#                 out_img = gr.Image(type="pil",label="output")
-#                 seed_slider = gr.Slider(label="Seed Slider",elem_id="expand_mask_iteration_count", minimum=0, maximum=25647981548564, value=0, step=1)
-#                 grn_btn = gr.Button("image generation", elem_id="select_btn", variant="primary")
-#                 # bru_btn = gr.Button("Brush generation", elem_id="select_btn", variant="primary")
-#             with gr.Column():
-#                 scheduler = gr.Dropdown(choices=["DDIM","Euler","Euler a","UniPC","DPM2 Karras","DPM2 a Karras","PNDM","DPM++ 2M Karras","DPM++ 2M SDE Karras"],value = "Euler a",label="Sampler")
-#                 # lora_chk = gr.Checkbox(label="Use Lora", elem_id="invert_chk", show_label=True, value=False, interactive=True)
-#                 # image_out = gr.Image(type="pil",label="Output")
-#                 sam_image = gr.Image(label="Segment Anything image", elem_id="ia_sam_image", type="numpy", tool="sketch", brush_radius=8,
-#                                              show_label=False, interactive=True,height=400)
-#                 mask_btn = gr.Button("Create Mask", elem_id="select_btn", variant="primary")
-#                 with gr.Column():
-#                     with gr.Row():
-#                         invert_chk = gr.Checkbox(label="Invert mask", elem_id="invert_chk", show_label=True, value=True, interactive=True)
-#                         ignore_black_chk = gr.Checkbox(label="Ignore black area", elem_id="ignore_black_chk", value=True, show_label=True, interactive=True)
-#                         lora_chk = gr.Checkbox(label="Use Lora", elem_id="invert_chk", show_label=True, value=False, interactive=True)
-#                 with gr.Column():
-#                     sel_mask = gr.Image(label="Selected mask image", elem_id="ia_sel_mask", type="numpy", tool="sketch", brush_radius=12,
-#                                             show_label=False, interactive=True, height=480)
-#                 with gr.Column():
-#                     with gr.Row():
-#                         expand_mask_btn = gr.Button("Expand mask region", elem_id="expand_mask_btn")
-#                     # with gr.Column():
-#                         expand_mask_iteration_count = gr.Slider(label="Expand Mask Iterations",
-#                                                                     elem_id="expand_mask_iteration_count", minimum=1, maximum=100, value=1, step=1)
-#                     with gr.Row():
-#                         add_mask_btn = gr.Button("Add mask by sketch", elem_id="add_mask_btn")
-#                         apply_mask_btn = gr.Button("Trim mask by sketch", elem_id="apply_mask_btn")
-            
-
-    # run_btn.click(fn=run_seg,inputs=[input_image],outputs=[sam_image])
-    # mask_btn.click(fn=select_mask,inputs=[input_image, sam_image, invert_chk, ignore_black_chk,sel_mask], outputs=[sel_mask])
-    # expand_mask_btn.click(expand_mask, inputs=[input_image, sel_mask, expand_mask_iteration_count], outputs=[sel_mask])
-    # apply_mask_btn.click(apply_mask, inputs=[input_image, sel_mask], outputs=[sel_mask])
-    # add_mask_btn.click(add_mask, inputs=[input_image, sel_mask], outputs=[sel_mask])
-    # grn_btn.click(fn=generate_image,inputs=[input_image,sam_image,prompt,seed_slider,canny_slider,depth_slider,seg_slider,model_selection,scheduler,guidance_scale_slider,inference_slider,lora_chk],outputs=[out_img])
-    # bru_btn.click(fn=brush_geeration,inputs=[input_image,prompt],outputs=[out_img])
-# inpaint_anything_interface.launch()