vilarin commited on
Commit
a484b84
1 Parent(s): 2dc3f5b

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +22 -14
app.py CHANGED
@@ -1,17 +1,14 @@
1
  import os
2
  import gradio as gr
3
- #import torch
4
  import numpy as np
5
  import random
6
- #from diffusers import FluxPipeline
7
- from huggingface_hub import InferenceClient
8
  from translatepy import Translator
9
- #from huggingface_hub import hf_hub_download
10
  import requests
11
  import re
 
12
  from PIL import Image
13
 
14
- os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
15
  translator = Translator()
16
  HF_TOKEN = os.environ.get("HF_TOKEN", None)
17
  # Constants
@@ -31,7 +28,7 @@ JS = """function () {
31
  }
32
  }"""
33
 
34
- client = InferenceClient()
35
 
36
  def enable_lora(lora_in, lora_add):
37
  if not lora_in and not lora_add:
@@ -41,7 +38,13 @@ def enable_lora(lora_in, lora_add):
41
  lora_in = lora_add
42
  return lora_in
43
 
44
- def generate_image(
 
 
 
 
 
 
45
  prompt:str,
46
  model:str,
47
  width:int=768,
@@ -58,8 +61,8 @@ def generate_image(
58
  text = str(translator.translate(prompt, 'English'))
59
 
60
  #generator = torch.Generator().manual_seed(seed)
61
-
62
- image1 = client.text_to_image(
63
  prompt=text,
64
  height=height,
65
  width=width,
@@ -67,7 +70,10 @@ def generate_image(
67
  num_inference_steps=steps,
68
  model=basemodel,
69
  )
70
- image2 = client.text_to_image(
 
 
 
71
  prompt=text,
72
  height=height,
73
  width=width,
@@ -75,9 +81,11 @@ def generate_image(
75
  num_inference_steps=steps,
76
  model=model,
77
  )
 
 
78
  return image1, image2, seed
79
 
80
- def gen(
81
  prompt:str,
82
  lora_in:str="",
83
  lora_add:str="",
@@ -90,7 +98,7 @@ def gen(
90
  ):
91
  model = enable_lora(lora_in, lora_add)
92
  print(model)
93
- image1, image2, seed = generate_image(prompt,model,width,height,scales,steps,seed)
94
  return image1, image2, seed
95
 
96
 
@@ -128,8 +136,8 @@ with gr.Blocks(css=CSS, js=JS, theme="Nymbo/Nymbo_Theme") as demo:
128
  with gr.Row():
129
  with gr.Column(scale=4):
130
  with gr.Row():
131
- img1 = gr.Image(type="pil", label='flux Generated Image', height=600)
132
- img2 = gr.Image(type="pil", label='LoRA Generated Image', height=600)
133
  with gr.Row():
134
  prompt = gr.Textbox(label='Enter Your Prompt (Multi-Languages)', placeholder="Enter prompt...", scale=6)
135
  sendBtn = gr.Button(scale=1, variant='primary')
 
1
  import os
2
  import gradio as gr
 
3
  import numpy as np
4
  import random
5
+ from huggingface_hub import AsyncInferenceClient
 
6
  from translatepy import Translator
 
7
  import requests
8
  import re
9
+ import asyncio
10
  from PIL import Image
11
 
 
12
  translator = Translator()
13
  HF_TOKEN = os.environ.get("HF_TOKEN", None)
14
  # Constants
 
28
  }
29
  }"""
30
 
31
+ client = AsyncInferenceClient()
32
 
33
  def enable_lora(lora_in, lora_add):
34
  if not lora_in and not lora_add:
 
38
  lora_in = lora_add
39
  return lora_in
40
 
41
+ def imagename():
42
+ os.makedirs("output", exist_ok=True)
43
+ base_count = len(glob(os.path.join("output", "*.webp")))
44
+ image_path = os.path.join("output", f"{base_count:06d}.webp")
45
+ return image_path
46
+
47
+ async def generate_image(
48
  prompt:str,
49
  model:str,
50
  width:int=768,
 
61
  text = str(translator.translate(prompt, 'English'))
62
 
63
  #generator = torch.Generator().manual_seed(seed)
64
+
65
+ image1 = await client.text_to_image(
66
  prompt=text,
67
  height=height,
68
  width=width,
 
70
  num_inference_steps=steps,
71
  model=basemodel,
72
  )
73
+ image1=image1.save(imagename())
74
+ print(image1)
75
+
76
+ image2 = await client.text_to_image(
77
  prompt=text,
78
  height=height,
79
  width=width,
 
81
  num_inference_steps=steps,
82
  model=model,
83
  )
84
+ image2=image2.save(imagename())
85
+ print(image2)
86
  return image1, image2, seed
87
 
88
+ async def gen(
89
  prompt:str,
90
  lora_in:str="",
91
  lora_add:str="",
 
98
  ):
99
  model = enable_lora(lora_in, lora_add)
100
  print(model)
101
+ image1, image2, seed = await generate_image(prompt,model,width,height,scales,steps,seed)
102
  return image1, image2, seed
103
 
104
 
 
136
  with gr.Row():
137
  with gr.Column(scale=4):
138
  with gr.Row():
139
+ img1 = gr.Image(type="filepath", label='flux Generated Image', height=600)
140
+ img2 = gr.Image(type="filepath", label='LoRA Generated Image', height=600)
141
  with gr.Row():
142
  prompt = gr.Textbox(label='Enter Your Prompt (Multi-Languages)', placeholder="Enter prompt...", scale=6)
143
  sendBtn = gr.Button(scale=1, variant='primary')