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quantulr
2023-09-19 15:46:31 +08:00
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# Byte-compiled / optimized / DLL files
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MANIFEST
# PyInstaller
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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{
"[python]": {
"editor.defaultFormatter": "ms-python.black-formatter"
},
"python.formatting.provider": "none"
}

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import json
import cv2
import fastdeploy as fd
import requests
from fastdeploy.serving.utils import cv2_to_base64
if __name__ == "__main__":
url = "http://127.0.0.1:8000/fd/yolov5s"
headers = {"Content-Type": "application/json"}
im = cv2.imread("origin.jpg")
print(cv2_to_base64(im))
data = {"data": {"image": cv2_to_base64(im)}, "parameters": {}}
resp = requests.post(url=url, headers=headers, data=json.dumps(data))
if resp.status_code == 200:
r_json = json.loads(resp.json()["result"])
det_result = fd.vision.utils.json_to_detection(r_json)
vis_im = fd.vision.vis_detection(im, det_result, score_threshold=0.5)
cv2.imwrite("visualized_result.jpg", vis_im)
print("Visualized result save in ./visualized_result.jpg")
else:
print("Error code:", resp.status_code)
print(resp.text)

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import asyncio
import io
import json
import aiohttp
import cv2
import fastdeploy as fd
import numpy as np
from fastapi import APIRouter, HTTPException, UploadFile
from fastapi.responses import StreamingResponse
from fastdeploy.serving.utils import cv2_to_base64
from image_identification.model import model_instance
router = APIRouter(prefix="/image")
async def request(url: str, data, headers):
async with aiohttp.ClientSession() as session:
async with session.post(url=url, data=data, headers=headers) as response:
return await response.json()
@router.post("/get_visuallized_image")
async def getVisualized_image(image: UploadFile):
contents = await image.read()
nparr = np.fromstring(contents, np.uint8)
im = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
url = "http://127.0.0.1:8000/fd/yolov5s"
headers = {"Content-Type": "application/json"}
data = {"data": {"image": cv2_to_base64(im)}, "parameters": {}}
try:
resp = await asyncio.gather(
*[request(url=url, data=json.dumps(data), headers=headers)]
)
r_json = json.loads(resp[0]["result"])
det_result = fd.vision.utils.json_to_detection(r_json)
vis_im = fd.vision.vis_detection(im, det_result, score_threshold=0.5)
_res, im_jpg = cv2.imencode(".jpg", vis_im)
return StreamingResponse(io.BytesIO(im_jpg.tobytes()), media_type="image/jpeg")
except:
raise HTTPException(status_code=500, detail="获取失败")
@router.post("/analyze", tags=["analyze"])
async def analyze(image: UploadFile):
image_content = await image.read()
nparr = np.fromstring(image_content, np.uint8)
im = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
result = model_instance.predict(im)
vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
im_jpg = cv2.imencode(".jpg", vis_im)[1]
return StreamingResponse(io.BytesIO(im_jpg.tobytes()), media_type="image/jpeg")

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import logging
import os
import fastdeploy as fd
import uvicorn
from fastdeploy.serving.server import SimpleServer
from .controllers import image
from .model import model_instance
logging.getLogger().setLevel(logging.INFO)
print(model_instance)
# Create server, setup REST API
app = SimpleServer()
app.register(
task_name="fd/yolov5s",
model_handler=fd.serving.handler.VisionModelHandler,
predictor=model_instance,
)
app.include_router(image.router)
def runApp():
uvicorn.run("image_identification.main:app", host="0.0.0.0", port=8000, reload=True)

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from .model import model_instance

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import os
import fastdeploy as fd
# Configurations
model_dir = "yolov5s_infer"
device = "cpu"
use_trt = False
# Prepare model
model_file = os.path.join(model_dir, "model.pdmodel")
params_file = os.path.join(model_dir, "model.pdiparams")
# Setup runtime option to select hardware, backend, etc.
option = fd.RuntimeOption()
if device.lower() == "gpu":
option.use_gpu()
if use_trt:
option.use_trt_backend()
option.set_trt_input_shape("images", [1, 3, 640, 640])
option.set_trt_cache_file("yolov5s.trt")
# Create model instance
model_instance = fd.vision.detection.YOLOv5(
model_file, params_file, runtime_option=option, model_format=fd.ModelFormat.PADDLE
)

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[tool.poetry]
name = "image-identification"
version = "0.1.0"
description = ""
authors = ["quantulr <35954003+quantulr@users.noreply.github.com>"]
readme = "README.md"
[tool.poetry.dependencies]
python = ">=3.9,<3.13"
fastdeploy-python = {url = "https://bj.bcebos.com/fastdeploy/release/wheels/fastdeploy_python-1.0.7-cp39-cp39-macosx_10_14_x86_64.whl"}
numpy = "^1.26.0"
opencv-python = "^4.8.0.76"
python-multipart = "^0.0.6"
aiohttp = "^3.8.5"
sqlalchemy = "^2.0.21"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
[tool.poetry.scripts]
serve = "image_identification.main:runApp"

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