aidlab/AiDA_Python
6
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

feat（新功能）:

Browse Source 
fix（修复bug）:
docs（文档变更）:
refactor（重构）:
test(增加测试): 旧版product 测试
This commit is contained in:
zhouchengrong
2025-02-03 19:36:56 +08:00
parent 74008c4586
commit 48ae1cfb75
1 changed files with 10 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
app/service/generate_image/service_generate_product_image.py
View File

@@ -247,7 +247,10 @@ class GenerateProductImage:
self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
else:
# pil图像转成numpy数组
image = result.as_numpy("generated_inpaint_image")
if self.product_type == "single":
image = result.as_numpy("generated_cnet_image")
else:
image = result.as_numpy("generated_inpaint_image")
image_result = Image.fromarray(np.squeeze(image.astype(np.uint8)))
# cropped_image = post_processing_image(image_result, self.left, self.top)
image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png")
@@ -269,9 +272,9 @@ class GenerateProductImage:
images = [self.image.astype(np.uint8)] * self.batch_size
if self.product_type == "single":
text_obj = np.array(prompts, dtype="object").reshape(-1, 1)
image_obj = np.array(images, dtype=np.uint8).reshape((-1, 1024, 1024, 3))
image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape(-1, 1)
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.uint8).reshape((-1, 768, 512, 3))
image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((-1, 1))
else:
text_obj = np.array(prompts, dtype="object").reshape((1))
image_obj = np.array(images, dtype=np.uint8).reshape((768, 512, 3))
@@ -290,7 +293,7 @@ class GenerateProductImage:
inputs = [input_text, input_image, input_image_strength]
if self.product_type == "single":
ctx = self.grpc_client.async_infer(model_name="stable_diffusion_xl_cnet_inpaint", inputs=inputs, callback=self.callback)
ctx = self.grpc_client.async_infer(model_name="stable_diffusion_1_5_cnet", inputs=inputs, callback=self.callback)
else:
ctx = self.grpc_client.async_infer(model_name="diffusion_ensemble_all", inputs=inputs, callback=self.callback)
@@ -369,8 +372,8 @@ if __name__ == '__main__':
# prompt="",
image_strength=0.7,
prompt="The best quality, masterpiece, real image.,high quality clothing details,8K realistic,HDR",
image_url="aida-users/11633/toProductImageElement/46166c36-c584-4e0f-b9fe-50615ec03ef3.png",
product_type="overall"
image_url="aida-results/result_40c7924e-e220-11ef-8ea2-0242ac150003.png",
product_type="single"
)
server = GenerateProductImage(rd)
print(server.get_result())