Hugging Face's logo

Spaces:
mdgh68
/
TRELLIS-Single3D
Runtime error

App Files Community
1
TRELLIS-Single3D
File size: 3,211 Bytes 
e538d2e
fd05616
 
 
 
 
e538d2e
fd05616
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6681bbb
fd05616
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c63008c
fd05616
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
 
import spaces
import numpy as np
from pixeloe.pixelize import pixelize
from PIL import Image
import gradio as gr

@spaces.GPU
def pixelize_image(
    image,
    downscale_mode="contrast",
    target_size=128,
    patch_size=16,
    thickness=2,
    color_matching=True,
    upscale=True
):
    """
    Apply pixelization effect to an image or batch of images.
    """
    if isinstance(image, Image.Image):
        image = np.array(image)
    
    processed = pixelize(
        image,
        mode=downscale_mode,
        target_size=target_size,
        patch_size=patch_size,
        thickness=thickness,
        contrast=1.0,
        saturation=1.0,
        color_matching=color_matching,
        no_upscale=not upscale
    )
    
    return Image.fromarray(processed)

def process_image(image, downscale_mode, target_size, patch_size, thickness, color_matching, upscale):
    if image is None:
        return None
    
    result = pixelize_image(
        image,
        downscale_mode=downscale_mode,
        target_size=target_size,
        patch_size=patch_size,
        thickness=thickness,
        color_matching=color_matching,
        upscale=upscale
    )
    
    return result

def create_pixelize_tab():
    with gr.Tab("Pixelizer"):
        
        with gr.Row():
            with gr.Column():
                input_image = gr.Image(label="Input Image", type="pil", height=256)
                
                downscale_mode = gr.Dropdown(
                    choices=["contrast", "bicubic", "nearest", "center", "k-centroid"],
                    value="contrast",
                    label="Downscale Mode"
                )
                
                target_size = gr.Slider(
                    minimum=8,
                    maximum=1024,
                    value=128,
                    step=8,
                    label="Target Size"
                )
                
                patch_size = gr.Slider(
                    minimum=4,
                    maximum=32,
                    value=16,
                    step=2,
                    label="Patch Size"
                )
                
                thickness = gr.Slider(
                    minimum=1,
                    maximum=16,
                    value=2,
                    step=1,
                    label="Thickness"
                )
                
                color_matching = gr.Checkbox(
                    value=True,
                    label="Color Matching"
                )
                
                upscale = gr.Checkbox(
                    value=True,
                    label="Upscale"
                )
                
                process_btn = gr.Button("Process Image")
            
            with gr.Column():
                output_image = gr.Image(label="Processed Image")
        
        # Set up processing event
        process_btn.click(
            fn=process_image,
            inputs=[
                input_image,
                downscale_mode,
                target_size,
                patch_size,
                thickness,
                color_matching,
                upscale
            ],
            outputs=output_image
        )