update app

README.md

@@ -1,6 +1,6 @@
 ---
 title: Dreambooth Bored Ape
-emoji: 🏢
+emoji: 🐵
 colorFrom: red
 colorTo: pink
 sdk: gradio
@@ -8,6 +8,11 @@ sdk_version: 3.23.0
 app_file: app.py
 pinned: false
 license: creativeml-openrail-m
+tags:
+  - keras-dreambooth
+  - scifi
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+---

app.py

@@ -0,0 +1,119 @@
+from huggingface_hub import from_pretrained_keras
+from keras_cv import models
+import gradio as gr
+
+from tensorflow import keras
+
+from diffusers import StableDiffusionPipeline
+
+keras.mixed_precision.set_global_policy("mixed_float16")
+
+# prepare model
+resolution = 512
+
+# checkpoint of the converted Stable Diffusion from KerasCV
+model_ckpt = "nielsgl/dreambooth-bored-ape"
+pipeline = StableDiffusionPipeline.from_pretrained(model_ckpt)
+pipeline.to("cuda")
+
+unique_id = "drawbayc"
+class_label = "monkey"
+prompt = f"A drawing of {unique_id} {class_label} as a cowboy"
+image = pipeline(prompt, num_inference_steps=50).images[0]
+
+# generate images
+def infer(prompt, negative_prompt, guidance_scale=10, num_inference_steps=50):
+    neg = negative_prompt if negative_prompt else None
+    imgs = []
+    while len(imgs) != 2:
+        next_prompt = pipeline(prompt, negative_prompt=neg, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps, num_images_per_prompt=5)
+        for img, is_neg in zip(next_prompt.images, next_prompt.nsfw_content_detected):
+            if not is_neg:
+                imgs.append(img)
+            if len(imgs) == 2:
+                break
+            
+    return imgs
+    
+output = gr.Gallery(label="Outputs").style(grid=(1,2))
+
+# customize interface
+title = "KerasCV Stable Diffusion Demo on images of Bored Apes."
+description = "This is a dreambooth model fine-tuned on images the NFT collection of the Bored Ape Yacht Club. To try it, input the concept with `drawbayc ape`."
+examples=[
+    ["A drawing of a drawbayc ape as a cowboy", "", 12, 50],
+    ["A drawing of a drawbayc ape as a clown", "", 12, 50],
+    ["A drawing of a drawbayc ape as a turtle", "", 12, 50],
+
+]
+
+base_14 = "https://huggingface.co/nielsgl/dreambooth-bored-ape/resolve/main/"
+
+model_card_1 = f"""
+# KerasCV Stable Diffusion in Diffusers 🧨🤗
+
+# KerasCV Stable Diffusion in Diffusers 🧨🤗
+
+DreamBooth model for the `drawbayc ape` concept trained by nielsgl on the `nielsgl/bayc-tiny` dataset, images from this [Kaggle dataset](https://www.kaggle.com/datasets/stanleyjzheng/bored-apes-yacht-club).
+It can be used by modifying the `instance_prompt`: **a drawing of drawbayc ape**
+
+## Description
+
+The Stable Diffusion V2 pipeline contained in the corresponding repository (`nielsgl/dreambooth-bored-ape`) was created using a modified version of [this Space](https://huggingface.co/spaces/sayakpaul/convert-kerascv-sd-diffusers) for StableDiffusionV2 from KerasCV. The purpose is to convert the KerasCV Stable Diffusion weights in a way that is compatible with [Diffusers](https://github.com/huggingface/diffusers). This allows users to fine-tune using KerasCV and use the fine-tuned weights in Diffusers taking advantage of its nifty features (like [schedulers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/schedulers), [fast attention](https://huggingface.co/docs/diffusers/optimization/fp16), etc.).
+This model was created as part of the Keras DreamBooth Sprint 🔥. Visit the [organisation page](https://huggingface.co/keras-dreambooth) for instructions on how to take part!
+
+## Demo
+
+"""
+
+model_card_2 = f"""
+## Examples
+
+### Stable Diffusion V2.1
+
+## Examples
+
+> A drawing of drawbayc monkey dressed as an astronaut
+
+![a drawing of drawbayc monkey dressed as an astronaut]({base_14}examples/astronaut.jpg)
+
+> A drawing of drawbayc monkey dressed as the pope
+
+![> A drawing of drawbayc monkey dressed as an astronaut]({base_14}examples/pope.jpg)
+
+
+## Usage with Stable Diffusion V2.1
+
+```python
+from diffusers import StableDiffusionPipeline
+
+pipeline = StableDiffusionPipeline.from_pretrained('nielsgl/dreambooth-bored-ape')
+image = pipeline().images[0]
+image
+```
+
+"""
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        gr.Markdown(model_card_1)
+    with gr.Row():
+        with gr.Column():
+            prompt_pos = gr.Textbox(label="Positive Prompt", value="a drawing of drawbayc ape as an astronaut")
+            prompt_neg = gr.Textbox(label="Negative Prompt", value="bad anatomy, blurry")
+
+            prompt_gs = gr.Number(label='Guidance scale', value=12)
+            prompt_steps = gr.Slider(label="Inference Steps",value=50)
+            prompt_btn = gr.Button("Generate")
+        with gr.Column():
+            output = gr.Gallery(label="Outputs").style(grid=(1,2))
+    prompt_btn.click(infer, inputs=[prompt_pos, prompt_neg, prompt_gs, prompt_steps], outputs=[output])
+    with gr.Row():
+        gr.Examples(examples, inputs=[prompt_pos, prompt_neg, prompt_gs, prompt_steps], outputs=output, fn=infer, cache_examples=True)
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown(model_card_2)
+        with gr.Column():
+            gr.Markdown(" ")
+
+demo.queue().launch()

requirements.txt

@@ -0,0 +1,9 @@
+--extra-index-url https://download.pytorch.org/whl/cu113
+torch
+keras-cv
+tensorflow
+huggingface-hub
+diffusers
+transformers
+pycocotools
+accelerate