From fc982f6f04152c6e16fa51714a0e0e7002ca09e0 Mon Sep 17 00:00:00 2001 From: zhouchengrong Date: Mon, 10 Mar 2025 11:12:49 +0800 Subject: [PATCH] =?UTF-8?q?feat=EF=BC=88=E6=96=B0=E5=8A=9F=E8=83=BD?= =?UTF-8?q?=EF=BC=89:=20fix=EF=BC=88=E4=BF=AE=E5=A4=8Dbug=EF=BC=89:=20=20d?= =?UTF-8?q?esign=20=E9=80=89=E5=8C=BA=E9=A2=9C=E8=89=B2=E8=B0=83=E6=95=B4?= =?UTF-8?q?=20docs=EF=BC=88=E6=96=87=E6=A1=A3=E5=8F=98=E6=9B=B4=EF=BC=89:?= =?UTF-8?q?=20refactor=EF=BC=88=E9=87=8D=E6=9E=84=EF=BC=89:=20test(?= =?UTF-8?q?=E5=A2=9E=E5=8A=A0=E6=B5=8B=E8=AF=95):?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/service/design_fast/pipeline/color.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) diff --git a/app/service/design_fast/pipeline/color.py b/app/service/design_fast/pipeline/color.py index 3033bb5..d6c84e4 100644 --- a/app/service/design_fast/pipeline/color.py +++ b/app/service/design_fast/pipeline/color.py @@ -29,6 +29,24 @@ class Color: else: pattern = self.get_pattern(result['color']) resize_pattern = cv2.resize(pattern, (dim_image_w, dim_image_h), interpolation=cv2.INTER_AREA) + + if "partial_color" in result.keys() and result['partial_color'] != "": + bucket_name = result['partial_color'].split('/')[0] + object_name = result['partial_color'][result['partial_color'].find('/') + 1:] + partial_color = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="cv2") + h, w = partial_color.shape[0:2] + resize_pattern = cv2.resize(resize_pattern, (w, h), interpolation=cv2.INTER_AREA) + # 分离出 png 图的 alpha 通道 + alpha_channel = partial_color[:, :, 3] + # 提取 png 图的 RGB 通道 + png_rgb = partial_color[:, :, :3] + # 创建一个与 cv 图大小相同的掩码，用于指示哪些像素需要替换 + mask = alpha_channel > 0 + # 将掩码扩展为 3 通道，以便与 cv 图进行逐元素操作 + mask_3ch = np.stack([mask] * 3, axis=-1) + # 根据掩码将 png 图的颜色覆盖到 cv 图上 + resize_pattern[mask_3ch] = png_rgb[mask_3ch] + resize_pattern = cv2.resize(resize_pattern, (dim_image_w, dim_image_h), interpolation=cv2.INTER_AREA) closed_mo = np.expand_dims(result['mask'], axis=2).repeat(3, axis=2) gray_mo = np.expand_dims(result['gray'], axis=2).repeat(3, axis=2) get_image_fir = resize_pattern * (closed_mo / 255) * (gray_mo / 255)