Adding Train and Validation set

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+spc

app.py

@@ -0,0 +1,143 @@
+from diffusers import AutoPipelineForImage2Image, AutoPipelineForText2Image
+import torch
+import os
+
+try:
+    import intel_extension_for_pytorch as ipex
+except:
+    pass
+
+from PIL import Image
+import numpy as np
+import gradio as gr
+import psutil
+import time
+import math
+
+SAFETY_CHECKER = os.environ.get("SAFETY_CHECKER", None)
+TORCH_COMPILE = os.environ.get("TORCH_COMPILE", None)
+HF_TOKEN = os.environ.get("HF_TOKEN", None)
+# check if MPS is available OSX only M1/M2/M3 chips
+mps_available = hasattr(torch.backends, "mps") and torch.backends.mps.is_available()
+xpu_available = hasattr(torch, "xpu") and torch.xpu.is_available()
+device = torch.device(
+    "cuda" if torch.cuda.is_available() else "xpu" if xpu_available else "cpu"
+)
+torch_device = device
+torch_dtype = torch.float16
+
+print(f"SAFETY_CHECKER: {SAFETY_CHECKER}")
+print(f"TORCH_COMPILE: {TORCH_COMPILE}")
+print(f"device: {device}")
+
+if mps_available:
+    device = torch.device("mps")
+    torch_device = "cpu"
+    torch_dtype = torch.float32
+
+if SAFETY_CHECKER == "True":
+    i2i_pipe = AutoPipelineForImage2Image.from_pretrained(
+        "stabilityai/sdxl-turbo",
+        torch_dtype=torch_dtype,
+        variant="fp16" if torch_dtype == torch.float16 else "fp32",
+    )
+    t2i_pipe = AutoPipelineForText2Image.from_pretrained(
+        "stabilityai/sdxl-turbo",
+        torch_dtype=torch_dtype,
+        variant="fp16" if torch_dtype == torch.float16 else "fp32",
+    )
+else:
+    i2i_pipe = AutoPipelineForImage2Image.from_pretrained(
+        "stabilityai/sdxl-turbo",
+        safety_checker=None,
+        torch_dtype=torch_dtype,
+        variant="fp16" if torch_dtype == torch.float16 else "fp32",
+    )
+    t2i_pipe = AutoPipelineForText2Image.from_pretrained(
+        "stabilityai/sdxl-turbo",
+        safety_checker=None,
+        torch_dtype=torch_dtype,
+        variant="fp16" if torch_dtype == torch.float16 else "fp32",
+    )
+
+t2i_pipe.to(device=torch_device, dtype=torch_dtype).to(device)
+t2i_pipe.set_progress_bar_config(disable=True)
+i2i_pipe.to(device=torch_device, dtype=torch_dtype).to(device)
+i2i_pipe.set_progress_bar_config(disable=True)
+
+def resize_crop(image, size=512):
+    image = image.convert("RGB")
+    w, h = image.size
+    image = image.resize((size, int(size * (h / w))), Image.BICUBIC)
+    return image
+
+# Global variable to store the selected image index
+selected_image_index = None
+
+# Load images from the 'images' folder
+image_folder = 'images'
+images = [Image.open(os.path.join(image_folder, img)) for img in sorted(os.listdir(image_folder)) if img.endswith(('.png', '.jpg', '.jpeg'))]
+
+# Ensure that there are 34 images
+assert len(images) == 34, "There should be exactly 34 images in the 'images' folder."
+
+# Function to handle image selection
+async def select_fn(data: gr.SelectData, prompt: str):
+    global selected_image_index
+    selected_image_index = data.index
+    return await predict(prompt) 
+    
+async def predict(prompt):
+    global selected_image_index
+    strength = 0.49999999999999999
+    steps = 2
+    if selected_image_index is not None:
+        init_image = images[selected_image_index]
+        init_image = resize_crop(init_image)
+        generator = torch.manual_seed(123123)
+        last_time = time.time()
+    
+        if int(steps * strength) < 1:
+            steps = math.ceil(1 / max(0.10, strength))
+            
+        results = i2i_pipe(
+            prompt=prompt,
+            image=init_image,
+            generator=generator,
+            num_inference_steps=steps,
+            guidance_scale=0.0,
+            strength=strength,
+            width=512,
+            height=512,
+            output_type="pil",
+        )
+
+        print(f"Pipe took {time.time() - last_time} seconds")
+        nsfw_content_detected = (
+            results.nsfw_content_detected[0]
+            if "nsfw_content_detected" in results
+            else False
+        )
+        if nsfw_content_detected:
+            gr.Warning("NSFW content detected.")
+            return Image.new("RGB", (512, 512))
+        return results.images[0]
+
+# Create the Gradio interface
+with gr.Blocks() as app:
+    with gr.Row():
+        with gr.Column():
+            prompt = gr.Textbox(label="I see...")
+            image_gallery = gr.Gallery(value=images, columns=4)  # Adjust number of columns as needed
+        with gr.Column():
+            output = gr.Image(label="Generation")
+
+    button = gr.Button("Rorschachify!")
+
+    image_gallery.select(select_fn, inputs=[prompt], outputs=output, show_progress=False)
+    button.click(fn=predict, inputs=[prompt], outputs=output, show_progress=False)
+    prompt.change(fn=predict, inputs=[prompt], outputs=output, show_progress=False)
+
+# Run the app
+app.queue()
+app.launch()

requirements.txt

@@ -0,0 +1,80 @@
+accelerate==0.26.1
+aiofiles==23.2.1
+altair==5.2.0
+annotated-types==0.6.0
+anyio==4.2.0
+attrs==23.2.0
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.0
+cycler==0.12.1
+diffusers==0.25.1
+fastapi==0.109.0
+ffmpy==0.3.1
+filelock==3.13.1
+fonttools==4.47.2
+fsspec==2023.12.2
+gradio==4.15.0
+gradio_client==0.8.1
+h11==0.14.0
+httpcore==1.0.2
+httpx==0.26.0
+huggingface-hub==0.20.3
+idna==3.6
+importlib-metadata==7.0.1
+importlib-resources==6.1.1
+Jinja2==3.1.3
+jsonschema==4.21.1
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.4
+matplotlib==3.8.2
+mdurl==0.1.2
+mpmath==1.3.0
+networkx==3.0
+numpy==1.26.3
+orjson==3.9.12
+packaging==23.2
+pandas==2.2.0
+pillow==10.2.0
+psutil==5.9.8
+pydantic==2.5.3
+pydantic_core==2.14.6
+pydub==0.25.1
+Pygments==2.17.2
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-multipart==0.0.6
+pytz==2023.3.post1
+PyYAML==6.0.1
+referencing==0.32.1
+regex==2023.12.25
+requests==2.31.0
+rich==13.7.0
+rpds-py==0.17.1
+ruff==0.1.14
+safetensors==0.4.2
+semantic-version==2.10.0
+shellingham==1.5.4
+six==1.16.0
+sniffio==1.3.0
+starlette==0.35.1
+sympy==1.12
+tokenizers==0.15.1
+tomlkit==0.12.0
+toolz==0.12.1
+torch==2.1.2+cu118
+torchaudio==2.1.2+cu118
+torchvision==0.16.2+cu118
+tqdm==4.66.1
+transformers==4.37.0
+typer==0.9.0
+typing_extensions==4.9.0
+tzdata==2023.4
+urllib3==2.1.0
+uvicorn==0.27.0
+websockets==11.0.3
+zipp==3.17.0