From e0a69b7f632e570946741dd8e7686bf8b4fe1fa3 Mon Sep 17 00:00:00 2001 From: zhouchengrong Date: Thu, 18 Jul 2024 11:32:58 +0800 Subject: [PATCH] =?UTF-8?q?feat=20fix=20=E4=BF=AE=E5=A4=8D=E5=88=86?= =?UTF-8?q?=E5=89=B2=E5=90=8Eresize=E6=97=B6=20=E5=87=BA=E7=8E=B0=E7=9A=84?= =?UTF-8?q?=E6=8F=92=E5=80=BC=E9=97=AE=E9=A2=98=EF=BC=8C=E5=9B=A0=E4=B8=BA?= =?UTF-8?q?=E6=97=B6=E5=85=88=E5=A2=9E=E5=8A=A0=E9=80=8F=E6=98=8E=E9=80=9A?= =?UTF-8?q?=E9=81=93=EF=BC=8C=E7=84=B6=E5=90=8Eresize=20=E6=8F=92=E5=80=BC?= =?UTF-8?q?=E6=8A=8A=E8=BE=B9=E7=BC=98=E9=83=A8=E5=88=86=E4=BF=AE=E6=94=B9?= =?UTF-8?q?=E4=B8=BA=E5=8D=8A=E9=80=8F=E6=98=8E=20=E6=89=80=E4=BB=A5?= =?UTF-8?q?=E5=87=BA=E7=8E=B0=E7=BC=9D=E9=9A=99?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/service/design/items/pipelines/split.py | 33 +++++--------------- app/service/design/utils/conversion_image.py | 19 +++++++---- app/service/design/utils/synthesis_item.py | 15 ++++----- 3 files changed, 26 insertions(+), 41 deletions(-) diff --git a/app/service/design/items/pipelines/split.py b/app/service/design/items/pipelines/split.py index 7b010ab..efa20e4 100644 --- a/app/service/design/items/pipelines/split.py +++ b/app/service/design/items/pipelines/split.py @@ -42,39 +42,20 @@ class Split(object): else: back_mask = result['back_mask'] - rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), result['final_image'], result['mask']) + # rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), result['final_image'], front_mask + back_mask) + rgba_image = rgb_to_rgba(result['final_image'], front_mask + back_mask) + new_size = (int(rgba_image.shape[1] * result["scale"] * result["resize_scale"][0]), int(rgba_image.shape[0] * result["scale"] * result["resize_scale"][1])) + rgba_image = cv2.resize(rgba_image, new_size) result_front_image = np.zeros_like(rgba_image) + front_mask = cv2.resize(front_mask, new_size) result_front_image[front_mask != 0] = rgba_image[front_mask != 0] - # TODO PIL resize替换为CV2 - # result_front_image_pil = Image.fromarray(cvtColor(result_front_image, COLOR_BGR2RGBA)) - # front_new_size = (int(result_front_image_pil.width * result["scale"] * result["resize_scale"][0]), int(result_front_image_pil.height * result["scale"] * result["resize_scale"][1])) - # result_front_image_pil = result_front_image_pil.resize(front_new_size, Image.LANCZOS) - - front_new_size = (int(result_front_image.shape[1] * result["scale"] * result["resize_scale"][0]), int(result_front_image.shape[0] * result["scale"] * result["resize_scale"][1])) - result_front_image = cv2.resize(result_front_image, front_new_size) result_front_image_pil = Image.fromarray(cvtColor(result_front_image, COLOR_BGR2RGBA)) - - # result['front_mask_image'] = cv2.resize(front_mask, front_new_size) - # result['front_image'] = result_front_image_pil - front_mask = cv2.resize(front_mask, front_new_size) result['front_image'], result["front_image_url"], result["front_mask_url"] = upload_png_mask(result_front_image_pil, f'{generate_uuid()}', mask=front_mask) - if result["name"] in ('blouse', 'dress', 'outwear', 'tops'): result_back_image = np.zeros_like(rgba_image) + back_mask = cv2.resize(back_mask, new_size) result_back_image[back_mask != 0] = rgba_image[back_mask != 0] - # TODO PIL resize替换为CV2 - # result_back_image_pil = Image.fromarray(cvtColor(result_back_image, COLOR_BGR2RGBA)) - # back_new_size = (int(result_back_image_pil.width * result["scale"] * result["resize_scale"][0]), int(result_back_image_pil.height * result["scale"] * result["resize_scale"][1])) - # result_back_image_pil = result_back_image_pil.resize(back_new_size, Image.LANCZOS) - - back_new_size = (int(result_back_image.shape[1] * result["scale"] * result["resize_scale"][0]), int(result_back_image.shape[0] * result["scale"] * result["resize_scale"][1])) - result_back_image = cv2.resize(result_back_image, back_new_size) result_back_image_pil = Image.fromarray(cvtColor(result_back_image, COLOR_BGR2RGBA)) - - # result['back_mask_image'] = cv2.resize(back_mask, back_new_size) - # result['back_image'] = result_back_image_pil - - back_mask = cv2.resize(back_mask, back_new_size) result['back_image'], result["back_image_url"], result["back_mask_url"] = upload_png_mask(result_back_image_pil, f'{generate_uuid()}', mask=back_mask) else: result['back_image'] = None @@ -83,7 +64,7 @@ class Split(object): result['back_mask_image'] = None # 创建中间图层 - result_pattern_image_rgba = rgb_to_rgba((result['pattern_image'].shape[0], result['pattern_image'].shape[1]), result['pattern_image'], result['mask']) + result_pattern_image_rgba = rgb_to_rgba(result['pattern_image'], result['mask']) result_pattern_image_pil = Image.fromarray(cvtColor(result_pattern_image_rgba, COLOR_BGR2RGBA)) _, result['pattern_image_url'], _ = upload_png_mask(result_pattern_image_pil, f'{generate_uuid()}') return result diff --git a/app/service/design/utils/conversion_image.py b/app/service/design/utils/conversion_image.py index 77848cc..11e39ae 100644 --- a/app/service/design/utils/conversion_image.py +++ b/app/service/design/utils/conversion_image.py @@ -10,13 +10,20 @@ import numpy as np -def rgb_to_rgba(rgb_size, rgb_image, mask): - alpha_channel = np.full(rgb_size, 255, dtype=np.uint8) - # 创建四通道的结果图像 +# def rgb_to_rgba(rgb_size, rgb_image, mask): +# alpha_channel = np.full(rgb_size, 255, dtype=np.uint8) +# # 创建四通道的结果图像 +# rgba_image = np.dstack((rgb_image, alpha_channel)) +# alpha_channel = np.where(mask > 0, 255, 0) +# # 更新RGBA图像的透明度通道 +# rgba_image[:, :, 3] = alpha_channel +# return rgba_image + +def rgb_to_rgba(rgb_image, mask): + # 创建全透明的alpha通道 + alpha_channel = np.where(mask > 0, 255, 0).astype(np.uint8) + # 合并RGB图像和alpha通道 rgba_image = np.dstack((rgb_image, alpha_channel)) - alpha_channel = np.where(mask > 0, 255, 0) - # 更新RGBA图像的透明度通道 - rgba_image[:, :, 3] = alpha_channel return rgba_image diff --git a/app/service/design/utils/synthesis_item.py b/app/service/design/utils/synthesis_item.py index dc8e427..73d91c2 100644 --- a/app/service/design/utils/synthesis_item.py +++ b/app/service/design/utils/synthesis_item.py @@ -101,26 +101,23 @@ def synthesis(data, size): if layer['name'] != "body": test_image = Image.new('RGBA', size, (0, 0, 0, 0)) test_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image']) - mask_data = np.where(all_mask > 0, 255, 0).astype(np.uint8) - mask_alpha = Image.fromarray(mask_data) - cropped_image = Image.composite(test_image, Image.new("RGBA", test_image.size, (255, 255, 255, 0)), mask_alpha) - base_image.paste(cropped_image, (0, 0), cropped_image) + # mask_data = np.where(all_mask > 0, 255, 0).astype(np.uint8) + # mask_alpha = Image.fromarray(mask_data) + # cropped_image = Image.composite(test_image, Image.new("RGBA", test_image.size, (255, 255, 255, 0)), mask_alpha) + base_image.paste(test_image, (0, 0), test_image) else: base_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image']) result_image = base_image - with io.BytesIO() as output: - result_image.save(output, format='PNG') - data = output.getvalue() - image_data = io.BytesIO() result_image.save(image_data, format='PNG') image_data.seek(0) # oss upload image_bytes = image_data.read() - bucket_name = 'aida-results' + bucket_name = 'test' + # bucket_name= "aida-results" object_name = f'result_{generate_uuid()}.png' req = oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) return f"{bucket_name}/{object_name}"