gradio==5.6.0

.python-version

@@ -0,0 +1 @@
+3.10

README.md

@@ -4,8 +4,7 @@ emoji: 📉
 colorFrom: yellow
 colorTo: green
 sdk: gradio
-sdk_version: 3.45.2
-python_version: 3.10.11
+sdk_version: 5.6.0
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -27,7 +27,7 @@ if not torch.cuda.is_available():
 
 model = Model(base_model_id=DEFAULT_MODEL_ID, task_name="Canny")
 
-with gr.Blocks(css="style.css") as demo:
+with gr.Blocks(css_paths="style.css") as demo:
     gr.Markdown(DESCRIPTION)
     gr.DuplicateButton(
         value="Duplicate Space for private use",
@@ -36,29 +36,29 @@ with gr.Blocks(css="style.css") as demo:
     )
 
     with gr.Tabs():
-        with gr.TabItem("Canny"):
+        with gr.Tab("Canny"):
             create_demo_canny(model.process_canny)
-        with gr.TabItem("MLSD"):
+        with gr.Tab("MLSD"):
             create_demo_mlsd(model.process_mlsd)
-        with gr.TabItem("Scribble"):
+        with gr.Tab("Scribble"):
             create_demo_scribble(model.process_scribble)
-        with gr.TabItem("Scribble Interactive"):
+        with gr.Tab("Scribble Interactive"):
             create_demo_scribble_interactive(model.process_scribble_interactive)
-        with gr.TabItem("SoftEdge"):
+        with gr.Tab("SoftEdge"):
             create_demo_softedge(model.process_softedge)
-        with gr.TabItem("OpenPose"):
+        with gr.Tab("OpenPose"):
             create_demo_openpose(model.process_openpose)
-        with gr.TabItem("Segmentation"):
+        with gr.Tab("Segmentation"):
             create_demo_segmentation(model.process_segmentation)
-        with gr.TabItem("Depth"):
+        with gr.Tab("Depth"):
             create_demo_depth(model.process_depth)
-        with gr.TabItem("Normal map"):
+        with gr.Tab("Normal map"):
             create_demo_normal(model.process_normal)
-        with gr.TabItem("Lineart"):
+        with gr.Tab("Lineart"):
             create_demo_lineart(model.process_lineart)
-        with gr.TabItem("Content Shuffle"):
+        with gr.Tab("Content Shuffle"):
             create_demo_shuffle(model.process_shuffle)
-        with gr.TabItem("Instruct Pix2Pix"):
+        with gr.Tab("Instruct Pix2Pix"):
             create_demo_ip2p(model.process_ip2p)
 
     with gr.Accordion(label="Base model", open=False):
@@ -72,7 +72,7 @@ with gr.Blocks(css="style.css") as demo:
                 new_base_model_id = gr.Text(
                     label="New base model",
                     max_lines=1,
-                    placeholder="runwayml/stable-diffusion-v1-5",
+                    placeholder="stable-diffusion-v1-5/stable-diffusion-v1-5",
                     info="The base model must be compatible with Stable Diffusion v1.5.",
                     interactive=ALLOW_CHANGING_BASE_MODEL,
                 )
@@ -95,6 +95,7 @@ with gr.Blocks(css="style.css") as demo:
         inputs=new_base_model_id,
         outputs=current_base_model,
         api_name=False,
+        concurrency_id="main",
     )
 
 if __name__ == "__main__":

app_canny.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     num_samples = gr.Slider(
                         label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="canny",
+            concurrency_id="main",
         )
     return demo
 

app_depth.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["Midas", "DPT", "None"], type="value", value="DPT"
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="depth",
+            concurrency_id="main",
         )
     return demo
 

app_ip2p.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     num_samples = gr.Slider(
                         label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
@@ -58,23 +57,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="ip2p",
+            concurrency_id="main",
         )
     return demo
 

app_lineart.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor",
@@ -76,23 +75,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="lineart",
+            concurrency_id="main",
         )
     return demo
 

app_mlsd.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     num_samples = gr.Slider(
                         label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
@@ -70,23 +69,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="mlsd",
+            concurrency_id="main",
         )
     return demo
 

app_normal.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["NormalBae", "None"], type="value", value="NormalBae"
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="normal",
+            concurrency_id="main",
         )
     return demo
 

app_openpose.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button(label="Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["Openpose", "None"], type="value", value="Openpose"
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="openpose",
+            concurrency_id="main",
         )
     return demo
 

app_scribble.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["HED", "PidiNet", "None"], type="value", value="HED"
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="scribble",
+            concurrency_id="main",
         )
     return demo
 

app_scribble_interactive.py

@@ -13,8 +13,12 @@ from settings import (
 from utils import randomize_seed_fn
 
 
-def create_canvas(w, h):
-    return np.zeros(shape=(h, w, 3), dtype=np.uint8) + 255
+def create_canvas(w: int, h: int) -> dict[str, np.ndarray | list[np.ndarray]]:
+    return {
+        "background": np.full((h, w), 255, dtype=np.uint8),
+        "composite": np.full((h, w), 255, dtype=np.uint8),
+        "layers": [np.full((h, w), 255, dtype=np.uint8)],
+    }
 
 
 def create_demo(process):
@@ -36,9 +40,17 @@ def create_demo(process):
                     step=1,
                 )
                 create_button = gr.Button("Open drawing canvas!")
-                image = gr.Image(tool="sketch", brush_radius=10)
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                image = gr.ImageEditor(
+                    value=create_canvas(DEFAULT_IMAGE_RESOLUTION, DEFAULT_IMAGE_RESOLUTION),
+                    image_mode="L",
+                    width=MAX_IMAGE_RESOLUTION + 50,
+                    height=MAX_IMAGE_RESOLUTION + 50,
+                    sources=None,
+                    transforms=(),
+                    layers=False,
+                    brush=gr.Brush(default_size=2, default_color="black", color_mode="fixed"),
+                )
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     num_samples = gr.Slider(
                         label="Number of images", minimum=1, maximum=MAX_NUM_IMAGES, value=DEFAULT_NUM_IMAGES, step=1
@@ -92,17 +104,7 @@ def create_demo(process):
             inputs=inputs,
             outputs=result,
             api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
+            concurrency_id="main",
         )
     return demo
 

app_segmentation.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["UPerNet", "None"], type="value", value="UPerNet"
@@ -66,23 +65,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="segmentation",
+            concurrency_id="main",
         )
     return demo
 

app_shuffle.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor", choices=["ContentShuffle", "None"], type="value", value="ContentShuffle"
@@ -62,23 +61,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="content-shuffle",
+            concurrency_id="main",
         )
     return demo
 

app_softedge.py

@@ -17,8 +17,7 @@ def create_demo(process):
         with gr.Row():
             with gr.Column():
                 image = gr.Image()
-                prompt = gr.Textbox(label="Prompt")
-                run_button = gr.Button("Run")
+                prompt = gr.Textbox(label="Prompt", submit_btn=True)
                 with gr.Accordion("Advanced options", open=False):
                     preprocessor_name = gr.Radio(
                         label="Preprocessor",
@@ -75,23 +74,12 @@ def create_demo(process):
             outputs=seed,
             queue=False,
             api_name=False,
-        ).then(
-            fn=process,
-            inputs=inputs,
-            outputs=result,
-            api_name=False,
-        )
-        run_button.click(
-            fn=randomize_seed_fn,
-            inputs=[seed, randomize_seed],
-            outputs=seed,
-            queue=False,
-            api_name=False,
         ).then(
             fn=process,
             inputs=inputs,
             outputs=result,
             api_name="softedge",
+            concurrency_id="main",
         )
     return demo
 

model.py

@@ -40,7 +40,7 @@ def download_all_controlnet_weights() -> None:
 
 
 class Model:
-    def __init__(self, base_model_id: str = "runwayml/stable-diffusion-v1-5", task_name: str = "Canny"):
+    def __init__(self, base_model_id: str = "stable-diffusion-v1-5/stable-diffusion-v1-5", task_name: str = "Canny"):
         self.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
         self.base_model_id = ""
         self.task_name = ""
@@ -265,7 +265,7 @@ class Model:
     @torch.inference_mode()
     def process_scribble_interactive(
         self,
-        image_and_mask: dict[str, np.ndarray],
+        image_and_mask: dict[str, np.ndarray | list[np.ndarray]] | None,
         prompt: str,
         additional_prompt: str,
         negative_prompt: str,
@@ -282,7 +282,7 @@ class Model:
         if num_images > MAX_NUM_IMAGES:
             raise ValueError
 
-        image = image_and_mask["mask"]
+        image = 255 - image_and_mask["composite"]  # type: ignore
         image = HWC3(image)
         image = resize_image(image, resolution=image_resolution)
         control_image = PIL.Image.fromarray(image)

pyproject.toml

@@ -0,0 +1,22 @@
+[project]
+name = "controlnet-v1-1"
+version = "0.1.0"
+description = ""
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "accelerate>=1.1.1",
+    "controlnet-aux>=0.0.9",
+    "diffusers>=0.31.0",
+    "einops>=0.8.0",
+    "gradio>=5.6.0",
+    "hf-transfer>=0.1.8",
+    "mediapipe>=0.10.18",
+    "opencv-python-headless>=4.10.0.84",
+    "safetensors>=0.4.5",
+    "spaces>=0.30.4",
+    "torch==2.4.0",
+    "torchvision>=0.19.0",
+    "transformers>=4.46.3",
+    "xformers>=0.0.27.post2",
+]

requirements.txt

@@ -1,13 +1,370 @@
-accelerate==0.21.0
-controlnet_aux==0.0.6
-diffusers==0.18.2
-einops==0.6.1
-gradio==3.45.2
-huggingface-hub==0.16.4
-mediapipe==0.10.1
-opencv-python-headless==4.8.0.74
-safetensors==0.3.1
-torch==2.0.1
-torchvision==0.15.2
-transformers==4.30.2
-xformers==0.0.20
+# This file was autogenerated by uv via the following command:
+#    uv pip compile pyproject.toml -o requirements.txt
+absl-py==2.1.0
+    # via mediapipe
+accelerate==1.1.1
+    # via controlnet-v1-1 (pyproject.toml)
+aiofiles==23.2.1
+    # via gradio
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.6.2.post1
+    # via
+    #   gradio
+    #   httpx
+    #   starlette
+attrs==24.2.0
+    # via mediapipe
+certifi==2024.8.30
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+cffi==1.17.1
+    # via sounddevice
+charset-normalizer==3.4.0
+    # via requests
+click==8.1.7
+    # via
+    #   typer
+    #   uvicorn
+contourpy==1.3.1
+    # via matplotlib
+controlnet-aux==0.0.9
+    # via controlnet-v1-1 (pyproject.toml)
+cycler==0.12.1
+    # via matplotlib
+diffusers==0.31.0
+    # via controlnet-v1-1 (pyproject.toml)
+einops==0.8.0
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   controlnet-aux
+exceptiongroup==1.2.2
+    # via anyio
+fastapi==0.115.5
+    # via gradio
+ffmpy==0.4.0
+    # via gradio
+filelock==3.16.1
+    # via
+    #   controlnet-aux
+    #   diffusers
+    #   huggingface-hub
+    #   torch
+    #   transformers
+    #   triton
+flatbuffers==24.3.25
+    # via mediapipe
+fonttools==4.55.0
+    # via matplotlib
+fsspec==2024.10.0
+    # via
+    #   gradio-client
+    #   huggingface-hub
+    #   torch
+gradio==5.6.0
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   spaces
+gradio-client==1.4.3
+    # via gradio
+h11==0.14.0
+    # via
+    #   httpcore
+    #   uvicorn
+hf-transfer==0.1.8
+    # via controlnet-v1-1 (pyproject.toml)
+httpcore==1.0.7
+    # via httpx
+httpx==0.27.2
+    # via
+    #   gradio
+    #   gradio-client
+    #   safehttpx
+    #   spaces
+huggingface-hub==0.26.2
+    # via
+    #   accelerate
+    #   controlnet-aux
+    #   diffusers
+    #   gradio
+    #   gradio-client
+    #   tokenizers
+    #   transformers
+idna==3.10
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+imageio==2.36.0
+    # via scikit-image
+importlib-metadata==8.5.0
+    # via
+    #   controlnet-aux
+    #   diffusers
+jax==0.4.35
+    # via mediapipe
+jaxlib==0.4.35
+    # via
+    #   jax
+    #   mediapipe
+jinja2==3.1.4
+    # via
+    #   gradio
+    #   torch
+kiwisolver==1.4.7
+    # via matplotlib
+lazy-loader==0.4
+    # via scikit-image
+markdown-it-py==3.0.0
+    # via rich
+markupsafe==2.1.5
+    # via
+    #   gradio
+    #   jinja2
+matplotlib==3.9.2
+    # via mediapipe
+mdurl==0.1.2
+    # via markdown-it-py
+mediapipe==0.10.18
+    # via controlnet-v1-1 (pyproject.toml)
+ml-dtypes==0.5.0
+    # via
+    #   jax
+    #   jaxlib
+mpmath==1.3.0
+    # via sympy
+networkx==3.4.2
+    # via
+    #   scikit-image
+    #   torch
+numpy==1.26.4
+    # via
+    #   accelerate
+    #   contourpy
+    #   controlnet-aux
+    #   diffusers
+    #   gradio
+    #   imageio
+    #   jax
+    #   jaxlib
+    #   matplotlib
+    #   mediapipe
+    #   ml-dtypes
+    #   opencv-contrib-python
+    #   opencv-python-headless
+    #   pandas
+    #   scikit-image
+    #   scipy
+    #   tifffile
+    #   torchvision
+    #   transformers
+    #   xformers
+nvidia-cublas-cu12==12.1.3.1
+    # via
+    #   nvidia-cudnn-cu12
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-cuda-cupti-cu12==12.1.105
+    # via torch
+nvidia-cuda-nvrtc-cu12==12.1.105
+    # via torch
+nvidia-cuda-runtime-cu12==12.1.105
+    # via torch
+nvidia-cudnn-cu12==9.1.0.70
+    # via torch
+nvidia-cufft-cu12==11.0.2.54
+    # via torch
+nvidia-curand-cu12==10.3.2.106
+    # via torch
+nvidia-cusolver-cu12==11.4.5.107
+    # via torch
+nvidia-cusparse-cu12==12.1.0.106
+    # via
+    #   nvidia-cusolver-cu12
+    #   torch
+nvidia-nccl-cu12==2.20.5
+    # via torch
+nvidia-nvjitlink-cu12==12.6.77
+    # via
+    #   nvidia-cusolver-cu12
+    #   nvidia-cusparse-cu12
+nvidia-nvtx-cu12==12.1.105
+    # via torch
+opencv-contrib-python==4.10.0.84
+    # via mediapipe
+opencv-python-headless==4.10.0.84
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   controlnet-aux
+opt-einsum==3.4.0
+    # via jax
+orjson==3.10.11
+    # via gradio
+packaging==24.2
+    # via
+    #   accelerate
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   lazy-loader
+    #   matplotlib
+    #   scikit-image
+    #   spaces
+    #   transformers
+pandas==2.2.3
+    # via gradio
+pillow==11.0.0
+    # via
+    #   controlnet-aux
+    #   diffusers
+    #   gradio
+    #   imageio
+    #   matplotlib
+    #   scikit-image
+    #   torchvision
+protobuf==4.25.5
+    # via mediapipe
+psutil==5.9.8
+    # via
+    #   accelerate
+    #   spaces
+pycparser==2.22
+    # via cffi
+pydantic==2.9.2
+    # via
+    #   fastapi
+    #   gradio
+    #   spaces
+pydantic-core==2.23.4
+    # via pydantic
+pydub==0.25.1
+    # via gradio
+pygments==2.18.0
+    # via rich
+pyparsing==3.2.0
+    # via matplotlib
+python-dateutil==2.9.0.post0
+    # via
+    #   matplotlib
+    #   pandas
+python-multipart==0.0.12
+    # via gradio
+pytz==2024.2
+    # via pandas
+pyyaml==6.0.2
+    # via
+    #   accelerate
+    #   gradio
+    #   huggingface-hub
+    #   transformers
+regex==2024.11.6
+    # via
+    #   diffusers
+    #   transformers
+requests==2.32.3
+    # via
+    #   diffusers
+    #   huggingface-hub
+    #   spaces
+    #   transformers
+rich==13.9.4
+    # via typer
+ruff==0.7.4
+    # via gradio
+safehttpx==0.1.1
+    # via gradio
+safetensors==0.4.5
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   accelerate
+    #   diffusers
+    #   transformers
+scikit-image==0.24.0
+    # via controlnet-aux
+scipy==1.14.1
+    # via
+    #   controlnet-aux
+    #   jax
+    #   jaxlib
+    #   scikit-image
+semantic-version==2.10.0
+    # via gradio
+sentencepiece==0.2.0
+    # via mediapipe
+shellingham==1.5.4
+    # via typer
+six==1.16.0
+    # via python-dateutil
+sniffio==1.3.1
+    # via
+    #   anyio
+    #   httpx
+sounddevice==0.5.1
+    # via mediapipe
+spaces==0.30.4
+    # via controlnet-v1-1 (pyproject.toml)
+starlette==0.41.3
+    # via
+    #   fastapi
+    #   gradio
+sympy==1.13.3
+    # via torch
+tifffile==2024.9.20
+    # via scikit-image
+timm==0.6.7
+    # via controlnet-aux
+tokenizers==0.20.3
+    # via transformers
+tomlkit==0.12.0
+    # via gradio
+torch==2.4.0
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   accelerate
+    #   controlnet-aux
+    #   timm
+    #   torchvision
+    #   xformers
+torchvision==0.19.0
+    # via
+    #   controlnet-v1-1 (pyproject.toml)
+    #   controlnet-aux
+    #   timm
+tqdm==4.67.0
+    # via
+    #   huggingface-hub
+    #   transformers
+transformers==4.46.3
+    # via controlnet-v1-1 (pyproject.toml)
+triton==3.0.0
+    # via torch
+typer==0.13.1
+    # via gradio
+typing-extensions==4.12.2
+    # via
+    #   anyio
+    #   fastapi
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   pydantic
+    #   pydantic-core
+    #   rich
+    #   spaces
+    #   torch
+    #   typer
+    #   uvicorn
+tzdata==2024.2
+    # via pandas
+urllib3==2.2.3
+    # via requests
+uvicorn==0.32.0
+    # via gradio
+websockets==12.0
+    # via gradio-client
+xformers==0.0.27.post2
+    # via controlnet-v1-1 (pyproject.toml)
+zipp==3.21.0
+    # via importlib-metadata

settings.py

@@ -2,7 +2,7 @@ import os
 
 import numpy as np
 
-DEFAULT_MODEL_ID = os.getenv("DEFAULT_MODEL_ID", "ashllay/stable-diffusion-v1-5-archive")
+DEFAULT_MODEL_ID = os.getenv("DEFAULT_MODEL_ID", "stable-diffusion-v1-5/stable-diffusion-v1-5")
 
 MAX_NUM_IMAGES = int(os.getenv("MAX_NUM_IMAGES", "3"))
 DEFAULT_NUM_IMAGES = min(MAX_NUM_IMAGES, int(os.getenv("DEFAULT_NUM_IMAGES", "3")))