lposti commited on
Commit
753e694
·
1 Parent(s): 402fdb0

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +36 -20
app.py CHANGED
@@ -1,30 +1,46 @@
1
  from huggingface_hub import from_pretrained_keras
2
- from keras_cv import models
3
  import gradio as gr
4
-
5
  from tensorflow import keras
6
 
7
  keras.mixed_precision.set_global_policy("mixed_float16")
8
-
9
- # prepare model
10
  resolution = 256
11
- sd_dreambooth_model = models.StableDiffusion(
12
- img_width=resolution, img_height=resolution
13
- )
14
- db_diffusion_model = from_pretrained_keras("lposti/dreambooth-piranesi")
15
- sd_dreambooth_model._diffusion_model = db_diffusion_model
16
 
17
- # generate images
18
- def infer(prompt):
19
- generated_images = sd_dreambooth_model.text_to_image(
20
- prompt, batch_size=2
 
 
 
 
21
  )
22
- return generated_images
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
23
 
24
- output = gr.Gallery(label="Outputs").style(grid=(1,2))
 
 
25
 
26
- # customize interface
27
- title = "Dreambooth Piranesi"
28
- description = "This is a dreambooth model fine-tuned on the works of art of Giambattista Piranesi."
29
- examples=[["image of ancient city, in style sks"]]
30
- gr.Interface(infer, inputs=["text"], outputs=[output], title=title, description=description, examples=examples).queue().launch()
 
1
  from huggingface_hub import from_pretrained_keras
2
+ import keras_cv
3
  import gradio as gr
 
4
  from tensorflow import keras
5
 
6
  keras.mixed_precision.set_global_policy("mixed_float16")
7
+ # load keras model
 
8
  resolution = 256
9
+ dreambooth_model = keras_cv.models.StableDiffusion(
10
+ img_width=resolution, img_height=resolution, jit_compile=True,
11
+ )
12
+ loaded_diffusion_model = from_pretrained_keras("keras-dreambooth/dreambooth-piranesi")
13
+ dreambooth_model._diffusion_model = loaded_diffusion_model
14
 
15
+
16
+ def generate_images(prompt: str, negative_prompt:str, num_imgs_to_gen: int, ugs: int):
17
+ generated_img = dreambooth_model.text_to_image(
18
+ prompt,
19
+ negative_prompt=negative_prompt,
20
+ batch_size=num_imgs_to_gen,
21
+ num_steps=num_steps,
22
+ unconditional_guidance_scale=ugs,
23
  )
24
+
25
+ return generated_img
26
+
27
+ with gr.Blocks() as demo:
28
+ gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\"> Dreambooth Piranesi Art </h2>")
29
+ with gr.Row():
30
+ with gr.Column():
31
+ prompt = gr.Textbox(lines=1, value="image of monuments in sks style", label="Base Prompt")
32
+ negative_prompt = gr.Textbox(lines=1, value="deformed", label="Negative Prompt")
33
+ samples = gr.Slider(minimum=1, maximum=5, default=1, step=1, label="Number of Image")
34
+ num_steps = gr.Slider(label="Inference Steps",value=75)
35
+ ugs = gr.Slider(minimum=5, maximum=25, default=15, step=1, label="Unconditional Guidance Scale")
36
+ run = gr.Button(value="Run")
37
+ with gr.Column():
38
+ gallery = gr.Gallery(label="Outputs").style(grid=(1,2))
39
+
40
+ run.click(generate_images, inputs=[prompt,negative_prompt, samples, num_steps, ugs], outputs=gallery)
41
 
42
+ gr.Examples([["image of monuments in sks style, 8k, high quality, old paper","deformed", 1, 75, 15]],
43
+ [prompt,negative_prompt, samples,num_steps, ugs], gallery, generate_images)
44
+ # gr.Markdown('\n Demo created by: <a href=\"https://huggingface.co/kadirnar/\">Kadir Nar</a>')
45
 
46
+ demo.launch(debug=True)