Spaces:
Runtime error
Runtime error
File size: 3,695 Bytes
f2dbf59 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
import hashlib
import os
import time
from PIL import Image
from ..helper import encode_pil_to_base64, gen_frontend_mask
from ..plugins.anime_seg import AnimeSeg
from ..schema import RunPluginRequest, RemoveBGModel, InteractiveSegModel
from ..tests.utils import check_device, current_dir, save_dir
os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
import cv2
import pytest
from ..plugins import (
RemoveBG,
RealESRGANUpscaler,
GFPGANPlugin,
RestoreFormerPlugin,
InteractiveSeg,
)
img_p = current_dir / "bunny.jpeg"
img_bytes = open(img_p, "rb").read()
bgr_img = cv2.imread(str(img_p))
rgb_img = cv2.cvtColor(bgr_img, cv2.COLOR_BGR2RGB)
rgb_img_base64 = encode_pil_to_base64(Image.fromarray(rgb_img), 100, {})
bgr_img_base64 = encode_pil_to_base64(Image.fromarray(bgr_img), 100, {})
def _save(img, name):
cv2.imwrite(str(save_dir / name), img)
def test_remove_bg():
model = RemoveBG(RemoveBGModel.briaai_rmbg_1_4)
rgba_np_img = model.gen_image(
rgb_img, RunPluginRequest(name=RemoveBG.name, image=rgb_img_base64)
)
res = cv2.cvtColor(rgba_np_img, cv2.COLOR_RGBA2BGRA)
_save(res, "test_remove_bg.png")
bgr_np_img = model.gen_mask(
rgb_img, RunPluginRequest(name=RemoveBG.name, image=rgb_img_base64)
)
res_mask = gen_frontend_mask(bgr_np_img)
_save(res_mask, "test_remove_bg_frontend_mask.png")
assert len(bgr_np_img.shape) == 2
_save(bgr_np_img, "test_remove_bg_mask.jpeg")
def test_anime_seg():
model = AnimeSeg()
img = cv2.imread(str(current_dir / "anime_test.png"))
img_base64 = encode_pil_to_base64(Image.fromarray(img), 100, {})
res = model.gen_image(img, RunPluginRequest(name=AnimeSeg.name, image=img_base64))
assert len(res.shape) == 3
assert res.shape[-1] == 4
_save(res, "test_anime_seg.png")
res = model.gen_mask(img, RunPluginRequest(name=AnimeSeg.name, image=img_base64))
assert len(res.shape) == 2
_save(res, "test_anime_seg_mask.png")
@pytest.mark.parametrize("device", ["cuda", "cpu", "mps"])
def test_upscale(device):
check_device(device)
model = RealESRGANUpscaler("realesr-general-x4v3", device)
res = model.gen_image(
rgb_img,
RunPluginRequest(name=RealESRGANUpscaler.name, image=rgb_img_base64, scale=2),
)
_save(res, f"test_upscale_x2_{device}.png")
res = model.gen_image(
rgb_img,
RunPluginRequest(name=RealESRGANUpscaler.name, image=rgb_img_base64, scale=4),
)
_save(res, f"test_upscale_x4_{device}.png")
@pytest.mark.parametrize("device", ["cuda", "cpu", "mps"])
def test_gfpgan(device):
check_device(device)
model = GFPGANPlugin(device)
res = model.gen_image(
rgb_img, RunPluginRequest(name=GFPGANPlugin.name, image=rgb_img_base64)
)
_save(res, f"test_gfpgan_{device}.png")
@pytest.mark.parametrize("device", ["cuda", "cpu", "mps"])
def test_restoreformer(device):
check_device(device)
model = RestoreFormerPlugin(device)
res = model.gen_image(
rgb_img, RunPluginRequest(name=RestoreFormerPlugin.name, image=rgb_img_base64)
)
_save(res, f"test_restoreformer_{device}.png")
@pytest.mark.parametrize("name", InteractiveSegModel.values())
@pytest.mark.parametrize("device", ["cuda", "cpu", "mps"])
def test_segment_anything(name, device):
check_device(device)
model = InteractiveSeg(name, device)
new_mask = model.gen_mask(
rgb_img,
RunPluginRequest(
name=InteractiveSeg.name,
image=rgb_img_base64,
clicks=([[448 // 2, 394 // 2, 1]]),
),
)
save_name = f"test_segment_anything_{name}_{device}.png"
_save(new_mask, save_name)
|