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update config

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This commit is contained in:
zhouchengrong
2024-03-11 14:49:01 +08:00
parent a13ae87e57
commit 077066607d
3 changed files with 923 additions and 851 deletions
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35
app/service/outfit_matcher/service.py
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@@ -1,3 +1,6 @@
import json
import os
import torch
import torch.nn.functional as F
import tritonclient.http as httpclient
@@ -5,14 +8,17 @@ import requests
import cv2
import numpy as np
from PIL import Image
from tqdm import tqdm
from app.service.outfit_matcher.dataset import FashionDataset
from app.service.outfit_matcher.foco import extract_main_colors
from app.service.outfit_matcher.outfit_evaluator import evaluate_outfits, visualize
class OutfitMatcherHon:
def __init__(self, outfits):
self.outfits = outfits
self.tritonclient = httpclient.InferenceServerClient(url="localhost:8000")
self.tritonclient = httpclient.InferenceServerClient(url="10.1.1.240:10010")
@staticmethod
def imnormalize(img, mean, std, to_rgb=True):
@@ -91,7 +97,7 @@ class OutfitMatcherHon:
for outfit in self.outfits:
images = []
colors = []
for item in outfit["items"]:
for item in outfit:
image = self.load_image(item["image_path"])
image = self.resize_image(image)
normalized_image = self.imnormalize(image,
@@ -108,7 +114,7 @@ class OutfitMatcherHon:
outfit_colors, _ = self.pad_array(outfit_colors)
return outfit_images, outfit_colors, mask
def get_result(self, outfits):
def get_result(self):
# start = time.time()
image, color, mask = self.preprocess()
# print(start - time.time())
@@ -126,8 +132,29 @@ class OutfitMatcherHon:
outputs = [
httpclient.InferRequestedOutput("output__0", binary_data=True),
]
results = self.tritonclient.infer(model_name="outfit_matcher", inputs=inputs, outputs=outputs)
results = self.tritonclient.infer(model_name="outfit_matcher_hon", inputs=inputs, outputs=outputs)
# 推理
# 取结果
inference_output1 = torch.from_numpy(results.as_numpy("output__0"))
return inference_output1 # Shape (N, 1)
if __name__ == '__main__':
with open("./test_param/recommendation_test.json", "r") as f:
param = json.load(f)
fashion_dataset = FashionDataset(param["database"])
for item in tqdm(param["query"]):
outfits = fashion_dataset.generate_outfit(item, param["topk"], param["max_outfits"])
service = OutfitMatcherHon(outfits=outfits)
scores = service.get_result()
visualize(outfits, scores, param["topk"], best=True,
output_path=os.path.join(
r"E:\workspace\outfit_matcher\2024 SS Outfit",
f"{item['item_name']}_best_{param['topk']}.png"
))
visualize(outfits, scores, param["topk"], best=False,
output_path=os.path.join(
r"E:\workspace\outfit_matcher\2024 SS Outfit",
f"{item['item_name']}_worst_{param['topk']}.png"
))
a = 1