app fixed

.idea/inspectionProfiles/Project_Default.xml

@@ -0,0 +1,83 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="DuplicatedCode" enabled="true" level="WEAK WARNING" enabled_by_default="true">
+      <Languages>
+        <language minSize="109" name="Python" />
+      </Languages>
+    </inspection_tool>
+    <inspection_tool class="Eslint" enabled="true" level="WARNING" enabled_by_default="true" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="55">
+            <item index="0" class="java.lang.String" itemvalue="torchmetrics" />
+            <item index="1" class="java.lang.String" itemvalue="albumentations_experimental" />
+            <item index="2" class="java.lang.String" itemvalue="OCHumanApi" />
+            <item index="3" class="java.lang.String" itemvalue="pytorchcv" />
+            <item index="4" class="java.lang.String" itemvalue="fire" />
+            <item index="5" class="java.lang.String" itemvalue="xmltodict" />
+            <item index="6" class="java.lang.String" itemvalue="Cython" />
+            <item index="7" class="java.lang.String" itemvalue="torch_optimizer" />
+            <item index="8" class="java.lang.String" itemvalue="gorilla" />
+            <item index="9" class="java.lang.String" itemvalue="timm" />
+            <item index="10" class="java.lang.String" itemvalue="smplx" />
+            <item index="11" class="java.lang.String" itemvalue="h5py" />
+            <item index="12" class="java.lang.String" itemvalue="torch" />
+            <item index="13" class="java.lang.String" itemvalue="imagesize" />
+            <item index="14" class="java.lang.String" itemvalue="mlflow" />
+            <item index="15" class="java.lang.String" itemvalue="pandas" />
+            <item index="16" class="java.lang.String" itemvalue="pytorch-lightning" />
+            <item index="17" class="java.lang.String" itemvalue="face_recognition" />
+            <item index="18" class="java.lang.String" itemvalue="hydra-core" />
+            <item index="19" class="java.lang.String" itemvalue="toolkit" />
+            <item index="20" class="java.lang.String" itemvalue="pytorch-toolbelt" />
+            <item index="21" class="java.lang.String" itemvalue="test_tube" />
+            <item index="22" class="java.lang.String" itemvalue="deepdish" />
+            <item index="23" class="java.lang.String" itemvalue="pycocotools" />
+            <item index="24" class="java.lang.String" itemvalue="albumentations" />
+            <item index="25" class="java.lang.String" itemvalue="scikit-learn" />
+            <item index="26" class="java.lang.String" itemvalue="cupy" />
+            <item index="27" class="java.lang.String" itemvalue="wheel" />
+            <item index="28" class="java.lang.String" itemvalue="chumpy" />
+            <item index="29" class="java.lang.String" itemvalue="numpy" />
+            <item index="30" class="java.lang.String" itemvalue="torchvision" />
+            <item index="31" class="java.lang.String" itemvalue="coloredlogs" />
+            <item index="32" class="java.lang.String" itemvalue="fastapi" />
+            <item index="33" class="java.lang.String" itemvalue="pydantic" />
+            <item index="34" class="java.lang.String" itemvalue="diffusers" />
+            <item index="35" class="java.lang.String" itemvalue="uvicorn" />
+            <item index="36" class="java.lang.String" itemvalue="Pillow" />
+            <item index="37" class="java.lang.String" itemvalue="transformers" />
+            <item index="38" class="java.lang.String" itemvalue="opencv-python" />
+            <item index="39" class="java.lang.String" itemvalue="rembg" />
+            <item index="40" class="java.lang.String" itemvalue="pyopengl" />
+            <item index="41" class="java.lang.String" itemvalue="safetensors" />
+            <item index="42" class="java.lang.String" itemvalue="mesh" />
+            <item index="43" class="java.lang.String" itemvalue="controlnet_aux" />
+            <item index="44" class="java.lang.String" itemvalue="xformers" />
+            <item index="45" class="java.lang.String" itemvalue="nltk" />
+            <item index="46" class="java.lang.String" itemvalue="matplotlib" />
+            <item index="47" class="java.lang.String" itemvalue="ultralytics" />
+            <item index="48" class="java.lang.String" itemvalue="accelerate" />
+            <item index="49" class="java.lang.String" itemvalue="compel" />
+            <item index="50" class="java.lang.String" itemvalue="tinydb" />
+            <item index="51" class="java.lang.String" itemvalue="gliner" />
+            <item index="52" class="java.lang.String" itemvalue="tensorflow" />
+            <item index="53" class="java.lang.String" itemvalue="kornia" />
+            <item index="54" class="java.lang.String" itemvalue="detectron2" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+    <inspection_tool class="PyUnresolvedReferencesInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredIdentifiers">
+        <list>
+          <option value="super.on_epoch_end" />
+          <option value="adhoc.demos.face_mesh_comparison.torch" />
+          <option value="pipeline.entities.Annotation.__getitem__" />
+        </list>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/vgg_heads.iml" filepath="$PROJECT_DIR$/.idea/vgg_heads.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

.idea/vgg_heads.iml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

app.py

@@ -1,146 +1,30 @@
-import gradio as gr
-import numpy as np
-import random
-from diffusers import DiffusionPipeline
-import torch
-
-device = "cuda" if torch.cuda.is_available() else "cpu"
+import uuid
 
-if torch.cuda.is_available():
-    torch.cuda.max_memory_allocated(device=device)
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
-    pipe.enable_xformers_memory_efficient_attention()
-    pipe = pipe.to(device)
-else: 
-    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
-    pipe = pipe.to(device)
+from fire import Fire
+from head_detector import HeadDetector
+import gradio as gr
 
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
+detector = HeadDetector()
 
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
 
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
-    
+def detect_faces(image):
+    image = detector(image).draw()
     return image
 
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css="""
-#col-container {
-    margin: 0 auto;
-    max-width: 520px;
-}
-"""
 
-if torch.cuda.is_available():
-    power_device = "GPU"
-else:
-    power_device = "CPU"
+iface = gr.Interface(
+    fn=detect_faces,
+    inputs=gr.inputs.Image(type="numpy", label="Upload an Image"),
+    outputs=gr.outputs.Image(type="numpy", label="Image with Faces"),
+    title="Demo of: VGGHeads: A Large-Scale Synthetic Dataset for 3D Human Heads",
+    description="Upload an image. The model performs simultaneous heads detection and head meshes reconstruction from a single image in a single step.",
+    allow_flagging='never',
+)
 
-with gr.Blocks(css=css) as demo:
-    
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(f"""
-        # Text-to-Image Gradio Template
-        Currently running on {power_device}.
-        """)
-        
-        with gr.Row():
-            
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            
-            run_button = gr.Button("Run", scale=0)
-        
-        result = gr.Image(label="Result", show_label=False)
 
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-                visible=False,
-            )
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
-            with gr.Row():
-                
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=512,
-                )
-            
-            with gr.Row():
-                
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,
-                )
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=12,
-                    step=1,
-                    value=2,
-                )
-        
-        gr.Examples(
-            examples = examples,
-            inputs = [prompt]
-        )
+def main():
+    iface.launch()
 
-    run_button.click(
-        fn = infer,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs = [result]
-    )
 
-demo.queue().launch()
+if __name__ == '__main__':
+    Fire(main)

requirements.txt

@@ -1,6 +1,2 @@
-accelerate
-diffusers
-invisible_watermark
-torch
-transformers
-xformers
+git+https://github.com/KupynOrest/head_detector.git
+fire