Update README.md

README.md

@@ -6,16 +6,89 @@ base_model:
 - black-forest-labs/FLUX.1-Canny-dev
 ---
 
-# Background
+# Introduction
+This model is fine-tuned based on black-forest-labs/FLUX.1-canny-dev. \
+The model enhances the performance when used with black-forest-labs/FLUX.1-Redux-dev. 
 
+# Examples
+## shoe/clothe generate demo
+![shoe/clothe generate demo](https://huggingface.co/woshin/FLUX.1-Canny-dev-redux/resolve/main/demo_1.jpg)
+## texture generate demo
+![texture generate demo](https://huggingface.co/woshin/FLUX.1-Canny-dev-redux/resolve/main/demo_2.jpg)
+## finetuned vs original
+![finetuned vs original](https://huggingface.co/woshin/FLUX.1-Canny-dev-redux/resolve/main/demo_3.jpg)
 
-# Short Introduction
+# Inference
+```
+import os
+import torch
+from diffusers import FluxPriorReduxPipeline, FluxPipeline, FluxControlPipeline, FluxTransformer2DModel
+from diffusers.utils import load_image
+from PIL import Image
 
+pipe_prior_redux = FluxPriorReduxPipeline.from_pretrained(
+  "black-forest-labs/FLUX.1-Redux-dev", 
+  torch_dtype=torch.bfloat16).to("cuda")
 
-# Examples
+pipe = FluxControlPipeline.from_pretrained(
+  "black-forest-labs/FLUX.1-Canny-dev", 
+  torch_dtype=torch.bfloat16
+).to("cuda")
+
+transformer = FluxTransformer2DModel.from_pretrained(
+  "woshin/FLUX.1-Canny-dev-redux",
+  subfolder="transformer",
+  torch_dtype=torch.bfloat16
+).to("cuda")
+
+pipe.transformer = transformer
 
-# Codes
-```
-hello world
-```
 
+def inference_control_redux(style_image, control_image, save_image, size=(1024, 1024)):
+  style_image = load_image(style_image).resize(size)
+  control_image = load_image(control_image).resize(size)
+  pipe_prior_redux_out = pipe_prior_redux(style_image, return_dict=False)
+  prompt_embeds, pooled_prompt_embeds = pipe_prior_redux_out[0], pipe_prior_redux_out[1]
+  image = pipe(
+    control_image=control_image,
+    height=size[1],
+    width=size[0],
+    num_inference_steps=50,
+    guidance_scale=30.0,
+    prompt_embeds=prompt_embeds,
+    pooled_prompt_embeds=pooled_prompt_embeds,
+  ).images[0]
+
+  dst = Image.new('RGB', (size[0] * 3, size[1]))
+  dst.paste(style_image, (0, 0))
+  dst.paste(control_image, (size[0], 0))
+  dst.paste(image, (size[0] * 2, 0))
+  dst.save(save_image)
+
+def inference_control(style_image, control_image, save_image, size=(1024, 1024)):
+  style_image = load_image(style_image).resize(size)
+  control_image = load_image(control_image).resize(size)
+  pipe_prior_redux_out = pipe_prior_redux(style_image, return_dict=False)
+  prompt_embeds, pooled_prompt_embeds = pipe_prior_redux_out[0], pipe_prior_redux_out[1]
+  image = pipe(
+    control_image=control_image,
+    height=size[1],
+    width=size[0],
+    num_inference_steps=50,
+    guidance_scale=30.0,
+    prompt_embeds=prompt_embeds,
+    pooled_prompt_embeds=pooled_prompt_embeds,
+  ).images[0]
+
+  dst = Image.new('RGB', (size[0] * 3, size[1]))
+  dst.paste(style_image, (0, 0))
+  dst.paste(control_image, (size[0], 0))
+  dst.paste(image, (size[0] * 2, 0))
+  dst.save(save_image)
+
+style_image = "style.png" # download from this repo
+control_image = "control.png"
+save_image = "save.png"
+inference_control_redux(style_image, control_image, save_image)
+
+```