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import os
import re
import uuid
import time
import dlib
import simplejson as json
import numpy as np
from flask import Blueprint, request, jsonify
from PIL import Image # todo: try to remove PIL dependency
# from app.models.sql_factory import load_sql_datasets, list_datasets, get_dataset, get_table
# from app.utils.im_utils import pil2np
from celery.result import AsyncResult
from app.server.tasks import celery
api_task = Blueprint('api_task', __name__)
@api_task.route('/')
def index():
"""Dummy index"""
return jsonify({})
# from flask import render_template, redirect, url_for, send_from_directory
# from flask import request, make_response, jsonify
# from . import main, utils
from app.server.tasks import task_lookup, list_active_tasks
# from PIL import Image, ImageOps
# import cv2 as cv
# import imutils
@api_task.route('/<task_name>/<task_id>')
def task_status(task_name, task_id):
"""Return celery image processing status"""
if task_name in task_lookup:
task = task_lookup[task_name]['task'].AsyncResult(task_id)
# task = AsyncResult(task_id, app=celery)
else:
return jsonify({
'state': 'error',
'percent': 100,
'message': 'Unknown task'
})
# app.logger.info('task state: {}'.format(task.state))
if task.state == 'PENDING':
response = {
'state': task.state,
'percent': 0,
'message': 'Pending...'
}
elif task.state != 'FAILURE':
response = {
'state': task.state,
'percent': task.info.get('percent', 0),
'uuid': task.info.get('uuid', 0),
'message': task.info.get('message', '')
}
if 'result' in task.info:
response['result'] = task.info['result']
else:
# something went wrong in the background job
response = {
'state': task.state,
'percent': 100,
'message': str(task.info), # this is the exception raised
}
return jsonify(response)
@api_task.route('/upload/sleep', methods=['GET', 'POST'])
def sleep_test():
async_task = task_lookup['sleep']['task'].apply_async(args=['sleep_test'])
task_url = '/task/{}/{}'.format('sleep', async_task.id)
return jsonify({
'result': True,
'task_url': task_url,
})
# @api_task.route('/upload', methods=['POST'])
# def upload():
# style = request.form['style']
# print('style',style)
# if style in task_lookup:
# task = task_lookup[style]['task']
# print('task',task)
# else:
# return jsonify({
# 'result': False,
# 'error': 'Unknown task',
# })
# file = request.files['user_image']
# agree = bool(request.form['agree'])
# ext = request.form['ext']
# if ext is None:
# ext = request.files['ext']
# uuid_name = str(uuid.uuid4())
# app.logger.info('[+] style: {}'.format(style))
# app.logger.info('[+] ext: {}'.format(ext))
# app.logger.info('[+] uuid_name: {}'.format(uuid_name))
# app.logger.info('[+] agreed: {}'.format(agree))
# # convert PNG to JPG
# print('[+] Resizing image')
# # LOL MaskRCNN needs to be run outside of the Celery Task
# im = Image.open(file.stream).convert('RGB')
# im = ImageOps.fit(im,(512,512))
# if agree:
# upload_folder = app.config['UPLOADS']
# else:
# upload_folder = app.config['UPLOADS_PRIVATE']
# fpath = os.path.join(upload_folder, uuid_name + '.jpg')
# # Save image to disk
# print('[+] Save image to {}'.format(fpath))
# im.save(fpath, 'JPEG', quality=100)
# im_pil_256 = im.resize((256,256))
# print('[+] ensure_np...')
# im_np = imx.ensure_np(im_pil_256)
# #print('[+] resize np...')
# #im_np = imutils.resize(im_np,width=256)
# upload_dir, render_dir, json_dir, upload_uri, render_uri = get_paths(agree)
# print('[+] Run mrcnn...')
# try:
# result = mask_rcnn.create_segmentations(im_np,concat=True)
# except:
# print('[-] Error. Could not run mask_rcnn')
# result = []
# if len(result) > 0:
# result = result[0]
# # save data, then pass to celery task
# print('[+] Save masks')
# seg_mask = result['seg_mask']
# fpath_seg_mask = os.path.join(render_dir, uuid_name + '_seg_mask.jpg')
# #cv.imwrite(fpath_seg_mask,cv.cvtColor(seg_mask,cv.COLOR_BGR2RGB))
# #seg_mask = seg_mask[:,:,::-1]
# seg_mask_pil = imx.ensure_pil(seg_mask)
# seg_mask_pil.save(fpath_seg_mask, 'JPEG', quality=100)
# im_mask = result['im_mask']
# fpath_im_mask = os.path.join(render_dir, uuid_name + '_im_mask.jpg')
# #im_mask = im_mask[:,:,::-1]
# im_mask_pil = imx.ensure_pil(im_mask)
# im_mask_pil.save(fpath_im_mask, 'JPEG',quality=100)
# #cv.imwrite(fpath_im_mask,cv.cvtColor(im_mask,cv.COLOR_BGR2RGB))
# celery_result = {
# 'score':str(result['score']),
# 'name':str(result['name']),
# 'class_index':str(result['class_index']),
# 'color':str(result['color']),
# 'fp_im_mask':fpath_im_mask,
# 'fp_seg_mask':fpath_seg_mask,
# 'valid':True
# }
# else:
# print('[-] no reults. process background only')
# celery_result = {
# 'score':None,
# 'name':None,
# 'class_index':None,
# 'color':None,
# 'fp_im_mask':None,
# 'fp_seg_mask':None,
# 'valid':False
# }
# print('[+] Start celery')
# async_task = task.apply_async(args=[uuid_name, agree, celery_result])
# task_url = url_for('main.task_status', task_name=style, task_id=async_task.id)
# return jsonify({
# 'result': True,
# 'task_url': task_url,
# 'uuid': uuid_name
# })
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