Irina Tolstykh
commited on
Commit
•
ce0031d
1
Parent(s):
71a75ca
update name
Browse files
app.py
CHANGED
@@ -7,7 +7,7 @@ import subprocess
|
|
7 |
if os.getenv('SYSTEM') == 'spaces':
|
8 |
GITHUB_TOKEN = os.getenv('GITHUB_TOKEN')
|
9 |
GITHUB_USER = os.getenv('GITHUB_USER')
|
10 |
-
git_repo = f"https://{GITHUB_TOKEN}@github.com/{GITHUB_USER}/
|
11 |
subprocess.call(shlex.split(f'pip install git+{git_repo}'))
|
12 |
|
13 |
import pathlib
|
@@ -18,7 +18,7 @@ import numpy as np
|
|
18 |
import functools
|
19 |
from dataclasses import dataclass
|
20 |
|
21 |
-
from
|
22 |
|
23 |
|
24 |
@dataclass
|
@@ -34,7 +34,7 @@ class Cfg:
|
|
34 |
DESCRIPTION = """
|
35 |
# MiVOLO: Multi-input Transformer for Age and Gender Estimation
|
36 |
|
37 |
-
This is an official demo.
|
38 |
"""
|
39 |
|
40 |
HF_TOKEN = os.getenv('HF_TOKEN')
|
@@ -84,9 +84,11 @@ def detect(
|
|
84 |
detected_objects, out_im = predictor.recognize(image)
|
85 |
return out_im[:, :, ::-1] # BGR -> RGB
|
86 |
|
|
|
87 |
def clear():
|
88 |
return None, 0.4, 0.7, "Use persons and faces", None
|
89 |
|
|
|
90 |
predictor = load_models()
|
91 |
|
92 |
image_dir = pathlib.Path('images')
|
|
|
7 |
if os.getenv('SYSTEM') == 'spaces':
|
8 |
GITHUB_TOKEN = os.getenv('GITHUB_TOKEN')
|
9 |
GITHUB_USER = os.getenv('GITHUB_USER')
|
10 |
+
git_repo = f"https://{GITHUB_TOKEN}@github.com/{GITHUB_USER}/MiVOLO.git"
|
11 |
subprocess.call(shlex.split(f'pip install git+{git_repo}'))
|
12 |
|
13 |
import pathlib
|
|
|
18 |
import functools
|
19 |
from dataclasses import dataclass
|
20 |
|
21 |
+
from mivolo.predictor import Predictor
|
22 |
|
23 |
|
24 |
@dataclass
|
|
|
34 |
DESCRIPTION = """
|
35 |
# MiVOLO: Multi-input Transformer for Age and Gender Estimation
|
36 |
|
37 |
+
This is an official demo for https://github.com/WildChlamydia/MiVOLO.
|
38 |
"""
|
39 |
|
40 |
HF_TOKEN = os.getenv('HF_TOKEN')
|
|
|
84 |
detected_objects, out_im = predictor.recognize(image)
|
85 |
return out_im[:, :, ::-1] # BGR -> RGB
|
86 |
|
87 |
+
|
88 |
def clear():
|
89 |
return None, 0.4, 0.7, "Use persons and faces", None
|
90 |
|
91 |
+
|
92 |
predictor = load_models()
|
93 |
|
94 |
image_dir = pathlib.Path('images')
|