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連接py

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桜華
2023-04-13 15:15:15 +08:00
parent f0fca2291c
commit 56c477d243
5 changed files with 122 additions and 11 deletions
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1
.gitignore vendored
View File

@@ -22,6 +22,7 @@
go.work go.work
data/ data/
venv/
.env .env
.env.example .env.example
main main

48
bin/main.go
View File

@@ -90,24 +90,58 @@ type ListView struct {
var mysqlConnection models.MysqlConnection var mysqlConnection models.MysqlConnection
var milvusConnection models.MilvusConnection var milvusConnection models.MilvusConnection
func GetNetWorkEmbedding(id int) (embedding []float32) {
host := viper.GetString("embedding.host")
port := viper.GetInt("embedding.port")
httpClient := &http.Client{}
request, err := http.NewRequest("PUT", fmt.Sprintf("http://%s:%d/reverse/%d", host, port, id), nil)
if err != nil {
log.Println("请求失败:", err)
return
}
response, err := httpClient.Do(request)
if err != nil {
log.Println("请求失败:", err)
return
}
defer response.Body.Close()
var result map[string]interface{}
err = json.NewDecoder(response.Body).Decode(&result)
if err != nil {
log.Println("解析失败:", err)
return
}
if result["code"] != 0 {
log.Println("请求失败:", result["message"])
return
}
embedding = result["feature"].([]float32)
return embedding
}
func (image *Image) GetSimilarImagesIdList(collection_name string) (ids []int64) { func (image *Image) GetSimilarImagesIdList(collection_name string) (ids []int64) {
ctx := context.Background() ctx := context.Background()
// 先从milvus中查询图片的向量 // 先从milvus中查询图片的向量
var embedding []float32
result, err := milvusConnection.Client.Query(ctx, collection_name, nil, fmt.Sprintf("id in [%d]", image.Id), []string{"embedding"}) result, err := milvusConnection.Client.Query(ctx, collection_name, nil, fmt.Sprintf("id in [%d]", image.Id), []string{"embedding"})
if err != nil { if err != nil {
log.Println("Milvus query failed:", err) log.Println("查詢向量失敗:", err)
return embedding = GetNetWorkEmbedding(image.Id)
} } else {
var embedding []float32
for _, item := range result { for _, item := range result {
if item.Name() == "embedding" { if item.Name() == "embedding" {
embedding = item.FieldData().GetVectors().GetFloatVector().Data embedding = item.FieldData().GetVectors().GetFloatVector().Data
continue continue
} }
} }
// TODO: 处理向量不存在的情况(生成) }
// TODO: 处理图片不存在的情况(404)
// 处理向量不存在的情况
if len(embedding) == 0 {
log.Println("向量不存在, 也未能重新生成")
return ids
}
// 用向量查询相似图片 // 用向量查询相似图片
topk := 1000 topk := 1000
@@ -115,7 +149,7 @@ func (image *Image) GetSimilarImagesIdList(collection_name string) (ids []int64)
vectors := []entity.Vector{entity.FloatVector(embedding)} vectors := []entity.Vector{entity.FloatVector(embedding)}
resultx, err := milvusConnection.Client.Search(ctx, collection_name, nil, "", []string{"id", "article_id"}, vectors, "embedding", entity.L2, topk, sp) resultx, err := milvusConnection.Client.Search(ctx, collection_name, nil, "", []string{"id", "article_id"}, vectors, "embedding", entity.L2, topk, sp)
if err != nil { if err != nil {
log.Println("Milvus search failed:", err) log.Println("搜索相似失敗:", err)
return return
} }

73
bin/resnet.py Normal file
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@@ -0,0 +1,73 @@
import json
import uuid
import towhee
from http.server import BaseHTTPRequestHandler, HTTPServer
img_path = './data/test.jpeg'
feat = towhee.glob(img_path).image_decode().image_embedding.timm(model_name='resnet50').tensor_normalize().to_list()
print(feat[0])
# 定義一個服務器類
class ResNetServer(BaseHTTPRequestHandler):
# 定義一個初始化方法
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# 定義一個處理 GET 請求的方法
def do_GET(self):
self.send_response(200) # 設置服務器響應的狀態碼
self.send_header('Content-type', 'text/html') # 設置服務器響應的標頭
self.end_headers() # 完成服務器響應的標頭
# 設置服務器響應的內容
self.wfile.write(bytes('''
<html>
<head>
<meta charset="utf-8">
<title>ResNet Server</title>
</head>
<body>
<h1>ResNet Server</h1>
// 這裡是一個簡單的服務器，可以接收圖像文件，並將圖像文件轉換為ResNet50的特徵向量
<form action="/" method="post" enctype="multipart/form-data">
<input type="file" name="file" />
<input type="submit" value="Upload" />
</form>
<p>Upload an image to get the prediction result.</p>
// 發送JSON格式的表單
</body>
</html>
''', 'utf-8'))
## 定義一個處理 POST 請求的方法
#def do_POST(self):
# self.send_response(200) # 設置服務器響應的狀態碼
# self.send_header('Content-type', 'application/json') # 設置服務器響應的標頭
# self.end_headers() # 完成服務器響應的標頭
# content_length = int(self.headers['Content-Length']) # 獲取請求的內容長度
# body = self.rfile.read(content_length) # 獲取請求的內容
# params = json.loads(body) # 將請求的內容解析為字典
# img_path = params['img_path'] # 獲取圖像的路徑
# feat = towhee.glob(img_path).image_decode().image_embedding.timm(model_name='resnet50').tensor_normalize().to_list()
# results = json.dumps(feat[0].tolist()) # 將結果轉換為JSON格式
# self.wfile.write(bytes(results, 'utf-8'))
# 定義一個處理 POST 請求的方法, 接收二進制圖像文件
def do_POST(self):
self.send_response(200) # 設置服務器響應的狀態碼
self.send_header('Content-type', 'application/json') # 設置服務器響應的標頭
self.end_headers() # 完成服務器響應的標頭
content_length = int(self.headers['Content-Length']) # 獲取請求的內容長度
body = self.rfile.read(content_length) # 獲取請求的內容
#img_path = './data/' + str(uuid.uuid4()) # 生成一個隨機的圖像文件名
#with open(img_path, 'wb') as f: # 將二進制圖像文件解碼為圖像數據保存在本地
# f.write(body)
feat = towhee.blob(body).image_decode().image_embedding.timm(model_name='resnet50').tensor_normalize().to_list()
results = json.dumps(feat[0].tolist()) # 將結果轉換為JSON格式
self.wfile.write(bytes(results, 'utf-8')) # 將結果發送給客戶端
# 判斷是否是直接執行該文件
if __name__ == '__main__':
HTTPServer(('0.0.0.0', 8000), ResNetServer).serve_forever()

1
go.mod
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@@ -38,6 +38,7 @@ require (
github.com/aliyun/aliyun-oss-go-sdk v2.2.7+incompatible github.com/aliyun/aliyun-oss-go-sdk v2.2.7+incompatible
github.com/chai2010/webp v1.1.1 github.com/chai2010/webp v1.1.1
github.com/go-sql-driver/mysql v1.7.0 github.com/go-sql-driver/mysql v1.7.0
github.com/sbinet/go-python v0.1.0
github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591 github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591
golang.org/x/image v0.0.0-20211028202545-6944b10bf410 // indirect golang.org/x/image v0.0.0-20211028202545-6944b10bf410 // indirect
) )

2
go.sum
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@@ -171,6 +171,8 @@ github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZN
github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA= github.com/prometheus/client_model v0.0.0-20190812154241-14fe0d1b01d4/go.mod h1:xMI15A0UPsDsEKsMN9yxemIoYk6Tm2C1GtYGdfGttqA=
github.com/rogpeppe/go-internal v1.3.0/go.mod h1:M8bDsm7K2OlrFYOpmOWEs/qY81heoFRclV5y23lUDJ4= github.com/rogpeppe/go-internal v1.3.0/go.mod h1:M8bDsm7K2OlrFYOpmOWEs/qY81heoFRclV5y23lUDJ4=
github.com/rogpeppe/go-internal v1.6.1 h1:/FiVV8dS/e+YqF2JvO3yXRFbBLTIuSDkuC7aBOAvL+k= github.com/rogpeppe/go-internal v1.6.1 h1:/FiVV8dS/e+YqF2JvO3yXRFbBLTIuSDkuC7aBOAvL+k=
github.com/sbinet/go-python v0.1.0 h1:WlS8dGoxKMt9/c54U4XQuVhQt79p0uJUdzopuDR4QaI=
github.com/sbinet/go-python v0.1.0/go.mod h1:Pq31TCdgxj39xSYY/VAfsWWrFphYSmx3jmPHtotzQNY=
github.com/sirupsen/logrus v1.4.2/go.mod h1:tLMulIdttU9McNUspp0xgXVQah82FyeX6MwdIuYE2rE= github.com/sirupsen/logrus v1.4.2/go.mod h1:tLMulIdttU9McNUspp0xgXVQah82FyeX6MwdIuYE2rE=
github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591 h1:dCWBD4Xchp/XFIR/x6D2l74DtQHvIpHsmpPRHgH9oUo= github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591 h1:dCWBD4Xchp/XFIR/x6D2l74DtQHvIpHsmpPRHgH9oUo=
github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591/go.mod h1:IXC7KN2FEuTEISdePm37qcFyXInAh6pfW35yDjbdfOM= github.com/sizeofint/gif-to-webp v0.0.0-20210224202734-e9d7ed071591/go.mod h1:IXC7KN2FEuTEISdePm37qcFyXInAh6pfW35yDjbdfOM=