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Diffstat (limited to 'megapixels/app/server/api_task.py')
| -rw-r--r-- | megapixels/app/server/api_task.py | 187 |
1 files changed, 187 insertions, 0 deletions
diff --git a/megapixels/app/server/api_task.py b/megapixels/app/server/api_task.py new file mode 100644 index 00000000..acdb5b7d --- /dev/null +++ b/megapixels/app/server/api_task.py @@ -0,0 +1,187 @@ +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 +# }) |