File size: 1,118 Bytes
d846043 3d3cb53 d846043 22bf258 3d3cb53 1e32e1a 3d3cb53 873b855 a740a6e 873b855 22bf258 96e0ac2 d846043 46c271a d846043 c56d19f d846043 0172050 d846043 |
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 |
import os
from typing import Dict, List, Any
import groundingdino
from groundingdino.util.inference import load_model, load_image, predict, annotate
import subprocess
# /app
HOME = os.getcwd()
# /opt/conda/lib/python3.9/site-packages/groundingdino
PACKAGE_HOME = os.path.dirname(groundingdino.__file__)
CONFIG_PATH = os.path.join(PACKAGE_HOME, "config", "GroundingDINO_SwinT_OGC.py")
WEIGHTS_PATH = os.path.join("model", "weights", "groundingdino_swint_ogc.pth")
class EndpointHandler():
def __init__(self, path):
# Preload all the elements you are going to need at inference.
self.model = load_model(CONFIG_PATH, path)
def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
data args:
inputs (:obj: `str` | `PIL.Image` | `np.array`)
kwargs
Return:
A :obj:`list` | `dict`: will be serialized and returned
"""
inputs = data.pop("inputs")
image = inputs.pop("image")
prompt = inputs.pop("prompt")
return [{
"image": image,
"prompt": prompt,
}]
|