robmarkcole
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deepstack-ui
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flask
Robin Cole 2019-09-17 05:59:22 +01:00
parent 50db745a97
commit 8d9322137c
4 changed files with 27 additions and 48 deletions
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3
.vscode/settings.json vendored Normal file
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{
"python.pythonPath": "venv/bin/python3"
}

5
README.md
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@ -9,5 +9,10 @@ $ source venv/bin/activate
$ pip install --upgrade -r requirements.txt
```
Now run:
```
$ python3 app/server.py serve
```
## References
* This code is a fork of https://github.com/render-examples/fastai-v3

62
app/server.py
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### Original -> https://github.com/render-examples/fastai-v3/blob/master/app/server.py
import aiohttp
import asyncio
import uvicorn
from fastai import *
from fastai.vision import *
from pathlib import Path
import sys
from io import BytesIO
from starlette.applications import Starlette
from starlette.middleware.cors import CORSMiddleware
from starlette.responses import HTMLResponse, JSONResponse
from starlette.staticfiles import StaticFiles
export_file_url = 'https://www.dropbox.com/s/6bgq8t6yextloqp/export.pkl?raw=1'
export_file_name = 'export.pkl'
classes = ['black', 'grizzly', 'teddys']
path = Path(__file__).parent
app = Starlette()
app.add_middleware(CORSMiddleware, allow_origins=['*'], allow_headers=['X-Requested-With', 'Content-Type'])
app.mount('/static', StaticFiles(directory='app/static'))
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_headers=["X-Requested-With", "Content-Type"],
)
app.mount("/static", StaticFiles(directory="app/static"))
async def download_file(url, dest):
if dest.exists(): return
async with aiohttp.ClientSession() as session:
async with session.get(url) as response:
data = await response.read()
with open(dest, 'wb') as f:
f.write(data)
async def setup_learner():
await download_file(export_file_url, path / export_file_name)
try:
learn = load_learner(path, export_file_name)
return learn
except RuntimeError as e:
if len(e.args) > 0 and 'CPU-only machine' in e.args[0]:
print(e)
message = "\n\nThis model was trained with an old version of fastai and will not work in a CPU environment.\n\nPlease update the fastai library in your training environment and export your model again.\n\nSee instructions for 'Returning to work' at https://course.fast.ai."
raise RuntimeError(message)
else:
raise
loop = asyncio.get_event_loop()
tasks = [asyncio.ensure_future(setup_learner())]
learn = loop.run_until_complete(asyncio.gather(*tasks))[0]
loop.close()
@app.route('/')
@app.route("/")
async def homepage(request):
html_file = path / 'view' / 'index.html'
html_file = path / "view" / "index.html"
return HTMLResponse(html_file.open().read())
@app.route('/analyze', methods=['POST'])
@app.route("/analyze", methods=["POST"])
async def analyze(request):
img_data = await request.form()
img_bytes = await (img_data['file'].read())
img_bytes = await (img_data["file"].read())
img = open_image(BytesIO(img_bytes))
prediction = learn.predict(img)[0]
return JSONResponse({'result': str(prediction)})
return JSONResponse({"result": str(prediction)})
if __name__ == '__main__':
if 'serve' in sys.argv:
uvicorn.run(app=app, host='0.0.0.0', port=5000, log_level="info")
if __name__ == "__main__":
if "serve" in sys.argv:
uvicorn.run(app=app, host="0.0.0.0", port=8000, log_level="info")

5
app/view/index.html
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<body>
<div>
<div class='center'>
<div class='title'>Classify Bear Images 🐻</div>
<div class='title'>Deepstack web UI</div>
<p>
Use images of <strong>teddy</strong> bears, <strong>black</strong> bears, <strong>grizzly</strong> bears, or
all three!
Repo: https://github.com/robmarkcole/deepstack-web-ui
</p>
<div class='content'>
<div class='no-display'>