diff options
Diffstat (limited to 'megapixels/app')
| -rw-r--r-- | megapixels/app/models/sql_factory.py | 180 | ||||
| -rw-r--r-- | megapixels/app/processors/faiss.py | 5 | ||||
| -rw-r--r-- | megapixels/app/server/api.py | 57 | ||||
| -rw-r--r-- | megapixels/app/server/api_task.py | 124 | ||||
| -rw-r--r-- | megapixels/app/server/create.py | 20 | ||||
| -rw-r--r-- | megapixels/app/server/tasks/__init__.py | 47 | ||||
| -rw-r--r-- | megapixels/app/server/tasks/blur.py | 81 | ||||
| -rw-r--r-- | megapixels/app/server/tasks/demo.py | 262 | ||||
| -rw-r--r-- | megapixels/app/server/tasks/sleep.py | 38 | ||||
| -rw-r--r-- | megapixels/app/settings/app_cfg.py | 7 | ||||
| -rw-r--r-- | megapixels/app/utils/im_utils.py | 12 |
11 files changed, 756 insertions, 77 deletions
diff --git a/megapixels/app/models/sql_factory.py b/megapixels/app/models/sql_factory.py index a580f28e..5b3cb5a3 100644 --- a/megapixels/app/models/sql_factory.py +++ b/megapixels/app/models/sql_factory.py @@ -3,7 +3,7 @@ import glob import time import pandas as pd -from sqlalchemy import create_engine, Table, Column, String, Integer, DateTime, Float +from sqlalchemy import create_engine, Table, Column, String, Integer, DateTime, Float, func from sqlalchemy.orm import sessionmaker from sqlalchemy.ext.declarative import declarative_base @@ -62,7 +62,8 @@ def load_sql_dataset(path, replace=False, engine=None, base_model=None): df = pd.read_csv(fn) # fix columns that are named "index", a sql reserved word df.reindex_axis(sorted(df.columns), axis=1) - df.columns = sorted(table.__table__.columns).keys() + columns = [column.name for column in table.__table__.columns] + df.columns = columns df.to_sql(name=table.__tablename__, con=engine, if_exists='replace', index=False) return dataset @@ -82,87 +83,153 @@ class SqlDataset: self.base_model = base_model def describe(self): + """ + List the available SQL tables for a given dataset. + """ return { 'name': self.name, 'tables': list(self.tables.keys()), } def get_identity(self, id): - table = self.get_table('identity_meta') + """ + Get an identity given an ID. + """ # id += 1 - identity = table.query.filter(table.image_id <= id).order_by(table.image_id.desc()).first().toJSON() + file_record_table = self.get_table('file_record') + file_record = file_record_table.query.filter(file_record_table.id == id).first() + + if not file_record: + return None + + identity_table = self.get_table('identity') + identity = identity_table.query.filter(identity_table.id == file_record.identity_id).first() + + if not identity: + return None + return { - 'uuid': self.select('uuids', id), - 'identity': identity, - 'roi': self.select('roi', id), - 'pose': self.select('pose', id), + 'file_record': file_record.toJSON(), + 'identity': identity.toJSON(), + 'face_roi': self.select('face_roi', id), + 'face_pose': self.select('face_pose', id), } def search_name(self, q): - table = self.get_table('identity_meta') - uuid_table = self.get_table('uuids') + """ + Find an identity by name. + """ + table = self.get_table('identity') + identity_list = table.query.filter(table.fullname.ilike(q)).order_by(table.fullname.desc()).limit(15) + return identity_list - identity = table.query.filter(table.fullname.like(q)).order_by(table.fullname.desc()).limit(30) + def search_description(self, q): + """ + Find an identity by description. + """ + table = self.get_table('identity') + identity_list = table.query.filter(table.description.ilike(q)).order_by(table.description.desc()).limit(15) + return identity_list + + def get_file_records_for_identities(self, identity_list): + """ + Given a list of identities, map these to file records. + """ identities = [] - for row in identity: - uuid = uuid_table.query.filter(uuid_table.id == row.image_id).first() - identities.append({ - 'uuid': uuid.toJSON(), - 'identity': row.toJSON(), - }) + file_record_table = self.get_table('file_record') + for row in identity_list: + file_record = file_record_table.query.filter(file_record_table.identity_id == row.id).first() + if file_record: + identities.append({ + 'file_record': file_record.toJSON(), + 'identity': row.toJSON(), + }) return identities def select(self, table, id): + """ + Perform a generic select. + """ table = self.get_table(table) if not table: return None session = Session() # for obj in session.query(table).filter_by(id=id): - # print(table) + # print(table) obj = session.query(table).filter(table.id == id).first() session.close() return obj.toJSON() def get_table(self, type): + """ + Get one of these memoized, dynamically generated tables. + """ if type in self.tables: return self.tables[type] - elif type == 'uuids': - self.tables[type] = self.uuid_table() - elif type == 'roi': - self.tables[type] = self.roi_table() - elif type == 'identity_meta': + elif type == 'file_record': + self.tables[type] = self.file_record_table() + elif type == 'identity': self.tables[type] = self.identity_table() - elif type == 'pose': - self.tables[type] = self.pose_table() + elif type == 'face_roi': + self.tables[type] = self.face_roi_table() + elif type == 'face_pose': + self.tables[type] = self.face_pose_table() else: return None return self.tables[type] - # ==> uuids.csv <== - # index,uuid - # 0,f03fd921-2d56-4e83-8115-f658d6a72287 - def uuid_table(self): - class UUID(self.base_model): - __tablename__ = self.name + "_uuid" + # ==> file_record.csv <== + # index,ext,fn,identity_key,sha256,subdir,uuid,identity_index + def file_record_table(self): + class FileRecord(self.base_model): + __tablename__ = self.name + "_file_record" id = Column(Integer, primary_key=True) + ext = Column(String(3, convert_unicode=True), nullable=False) + fn = Column(String(36, convert_unicode=True), nullable=False) + identity_key = Column(String(36, convert_unicode=True), nullable=False) + sha256 = Column(String(36, convert_unicode=True), nullable=False) + subdir = Column(String(36, convert_unicode=True), nullable=False) uuid = Column(String(36, convert_unicode=True), nullable=False) + identity_id = Column(Integer) def toJSON(self): return { 'id': self.id, 'uuid': self.uuid, + 'identity_id': self.identity_id, } - return UUID + return FileRecord - # ==> roi.csv <== + # ==> identity.csv <== + # index,description,gender,images,fullname + # 0,A. J. Cook,Canadian actress,f,1,0 + def identity_table(self): + class Identity(self.base_model): + __tablename__ = self.name + "_identity" + id = Column(Integer, primary_key=True) + description = Column(String(36, convert_unicode=True), nullable=False) + gender = Column(String(1, convert_unicode=True), nullable=False) + images = Column(Integer, nullable=False) + fullname = Column(String(36, convert_unicode=True), nullable=False) + def toJSON(self): + return { + 'id': self.id, + 'fullname': self.fullname, + 'images': self.images, + 'gender': self.gender, + 'description': self.description, + } + return Identity + + # ==> face_roi.csv <== # index,h,image_height,image_index,image_width,w,x,y # 0,0.33000000000000007,250,0,250,0.32999999999999996,0.33666666666666667,0.35 - def roi_table(self): - class ROI(self.base_model): + def face_roi_table(self): + class FaceROI(self.base_model): __tablename__ = self.name + "_roi" id = Column(Integer, primary_key=True) h = Column(Float, nullable=False) image_height = Column(Integer, nullable=False) - image_index = Column(Integer, nullable=False) + record_id = Column(Integer, nullable=False) image_width = Column(Integer, nullable=False) w = Column(Float, nullable=False) x = Column(Float, nullable=False) @@ -170,7 +237,7 @@ class SqlDataset: def toJSON(self): return { 'id': self.id, - 'image_index': self.image_index, + 'record_id': self.record_id, 'image_height': self.image_height, 'image_width': self.image_width, 'w': self.w, @@ -178,48 +245,25 @@ class SqlDataset: 'x': self.x, 'y': self.y, } - return ROI - - # ==> identity.csv <== - # index,fullname,description,gender,images,image_index - # 0,A. J. Cook,Canadian actress,f,1,0 - def identity_table(self): - class Identity(self.base_model): - __tablename__ = self.name + "_identity" - id = Column(Integer, primary_key=True) - fullname = Column(String(36, convert_unicode=True), nullable=False) - description = Column(String(36, convert_unicode=True), nullable=False) - gender = Column(String(1, convert_unicode=True), nullable=False) - images = Column(Integer, nullable=False) - image_id = Column(Integer, nullable=False) - def toJSON(self): - return { - 'id': self.id, - 'image_id': self.image_id, - 'fullname': self.fullname, - 'images': self.images, - 'gender': self.gender, - 'description': self.description, - } - return Identity + return FaceROI - # ==> pose.csv <== - # index,image_index,pitch,roll,yaw + # ==> face_pose.csv <== + # index,record_index,pitch,roll,yaw # 0,0,11.16264458441435,10.415885631337728,22.99719032415318 - def pose_table(self): - class Pose(self.base_model): + def face_pose_table(self): + class FacePose(self.base_model): __tablename__ = self.name + "_pose" id = Column(Integer, primary_key=True) - image_id = Column(Integer, primary_key=True) + record_id = Column(Integer, nullable=False) pitch = Column(Float, nullable=False) roll = Column(Float, nullable=False) yaw = Column(Float, nullable=False) def toJSON(self): return { 'id': self.id, - 'image_id': self.image_id, + 'record_id': self.record_id, 'pitch': self.pitch, 'roll': self.roll, 'yaw': self.yaw, } - return Pose + return FacePose diff --git a/megapixels/app/processors/faiss.py b/megapixels/app/processors/faiss.py index 5156ad71..0de8ec69 100644 --- a/megapixels/app/processors/faiss.py +++ b/megapixels/app/processors/faiss.py @@ -27,9 +27,12 @@ def build_all_faiss_databases(): build_faiss_database(name, DefaultRecipe()) def build_faiss_database(name, recipe): - vec_fn = os.path.join(cfg.DIR_FAISS_METADATA, name, "vecs.csv") + vec_fn = os.path.join(cfg.DIR_FAISS_METADATA, name, "face_vector.csv") index_fn = os.path.join(cfg.DIR_FAISS_INDEXES, name + ".index") + if not os.path.exists(vec_fn): + return + index = faiss.index_factory(recipe.dim, recipe.factory_type) keys, rows = load_csv_safe(vec_fn) diff --git a/megapixels/app/server/api.py b/megapixels/app/server/api.py index 3683d5fd..b3bce9bc 100644 --- a/megapixels/app/server/api.py +++ b/megapixels/app/server/api.py @@ -3,6 +3,7 @@ import re import time import dlib import numpy as np +import operator from flask import Blueprint, request, jsonify from PIL import Image # todo: try to remove PIL dependency @@ -27,7 +28,6 @@ def index(): """List the datasets and their fields""" return jsonify({ 'datasets': list_datasets() }) - @api.route('/dataset/<dataset_name>') def show(dataset_name): """Show the data that a dataset will return""" @@ -37,7 +37,6 @@ def show(dataset_name): else: return jsonify({ 'status': 404 }) - @api.route('/dataset/<dataset_name>/face', methods=['POST']) def upload(dataset_name): """Query an image against FAISS and return the matching identities""" @@ -108,9 +107,10 @@ def upload(dataset_name): for _d, _i in zip(distances, indexes): if _d <= THRESHOLD: dists.append(round(float(_d), 2)) - ids.append(_i+1) + ids.append(_i) - results = [ dataset.get_identity(int(_i)) for _i in ids ] + identities = [ dataset.get_identity(int(_i)) for _i in ids ] + identities = list(filter(None, identities)) # print(distances) # print(ids) @@ -127,7 +127,7 @@ def upload(dataset_name): # print(results) return jsonify({ 'query': query, - 'results': results, + 'results': identities, 'distances': dists, }) @@ -139,15 +139,56 @@ def name_lookup(dataset_name): dataset = get_dataset(dataset_name) q = request.args.get('q') - # print(q) + q = re.sub('[^a-zA-Z. ]+', '*', q) + terms = q.split(' ') query = { 'q': q, 'timing': time.time() - start, } - results = dataset.search_name(q + '%') if q else None + + if len(terms) == 0: + return jsonify({ 'query': query, 'results': [] }) + + lookup = {} + results_lookup = {} + + names = dataset.search_name(q + '%') + for name in names: + if name.id in lookup: + print(name.fullname) + lookup[name.id] += 4 + else: + print(name.fullname) + lookup[name.id] = 4 + results_lookup[name.id] = name - # print(results) + for i, term in enumerate(terms[0:5]): + search_term = '%' + term + '%' + names = dataset.search_name(search_term) if len(term) > 0 else [] + descriptions = dataset.search_description(search_term) if len(term) > 0 else [] + for name in names: + if name.id in lookup: + print(name.fullname) + lookup[name.id] += 2 + else: + print(name.fullname) + lookup[name.id] = 2 + results_lookup[name.id] = name + for name in descriptions: + if name.id in lookup: + print(name.fullname) + lookup[name.id] += 1 + else: + print(name.fullname) + lookup[name.id] = 1 + results_lookup[name.id] = name + + sorted_names = sorted(lookup.items(), key=operator.itemgetter(1), reverse=True)[0:10] + top_names = [results_lookup[item[0]] for item in sorted_names] + results = dataset.get_file_records_for_identities(top_names) + + print(results) return jsonify({ 'query': query, 'results': results, diff --git a/megapixels/app/server/api_task.py b/megapixels/app/server/api_task.py new file mode 100644 index 00000000..57ae9f7d --- /dev/null +++ b/megapixels/app/server/api_task.py @@ -0,0 +1,124 @@ +import os +import re +import uuid +import time +import dlib +import tempfile +import simplejson as json +import numpy as np +from flask import Blueprint, request, jsonify +from PIL import Image, ImageOps # todo: try to remove PIL dependency + +from celery.result import AsyncResult +from app.server.tasks import celery +from app.server.tasks import task_lookup, list_active_tasks +# from app.models.sql_factory import load_sql_datasets, list_datasets, get_dataset, get_table + +api_task = Blueprint('task', __name__) + +@api_task.route('/') +def index(): + """List active tasks""" + return jsonify(list_active_tasks) + +@api_task.route('/status/<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) + + if task_name not in task_lookup or task.info is None: + 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...', + 'data': task.info, + } + 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', ''), + 'data': task.info, + } + 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 + 'data': task.info, + } + return jsonify(response) + +@api_task.route('/upload/sleep', methods=['GET', 'POST']) +def sleep_test(): + """ + Test the Celery system using a task that sleeps. + """ + async_task = task_lookup['sleep']['task'].apply_async(args=['sleep_test']) + task_url = '/task/status/{}/{}'.format('sleep', async_task.id) + return jsonify({ + 'result': True, + 'task_url': task_url, + }) + +@api_task.route('/upload/blur', methods=['POST']) +def upload(): + return process('blur') + +@api_task.route('/upload/demo', methods=['POST']) +def demo(): + return process('demo') + +def process(style): + """ + Process an image in a particular style + """ + print('style: {}'.format(style)) + if style in task_lookup: + task = task_lookup[style]['task'] + print('task', task) + else: + return jsonify({ + 'result': False, + 'error': 'Unknown task', + }) + + print('get file...') + file = request.files['query_img'] + + uuid_str = str(uuid.uuid4()) + + print('[+] style: {}'.format(style)) + print('[+] uuid_name: {}'.format(uuid_str)) + + im = Image.open(file.stream).convert('RGB') + im = ImageOps.fit(im, (256, 256,)) + + tmpfile = tempfile.NamedTemporaryFile(delete=False) + + # Save image to disk + print('[+] Save image to temporary file') + im.save(tmpfile, 'JPEG', quality=80) + + print('[+] Start celery') + async_task = task.apply_async(args=[uuid_str, tmpfile.name]) + task_url = '/task/status/{}/{}'.format(style, async_task.id) + + return jsonify({ + 'result': True, + 'taskURL': task_url, + 'uuid': uuid_str + }) diff --git a/megapixels/app/server/create.py b/megapixels/app/server/create.py index 4b1333b9..a1ce56df 100644 --- a/megapixels/app/server/create.py +++ b/megapixels/app/server/create.py @@ -1,8 +1,25 @@ +import logging +import logging.handlers + +logger = logging.getLogger("") +logger.setLevel(logging.DEBUG) +handler = logging.handlers.RotatingFileHandler("flask.log", + maxBytes=3000000, backupCount=2) +formatter = logging.Formatter( + '[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s') +handler.setFormatter(formatter) +logger.addHandler(handler) +logging.getLogger().addHandler(logging.StreamHandler()) + +logging.debug("starting app") + from flask import Flask, Blueprint, jsonify, send_from_directory from flask_sqlalchemy import SQLAlchemy from app.models.sql_factory import connection_url, load_sql_datasets +from app.settings import app_cfg as cfg from app.server.api import api +from app.server.api_task import api_task db = SQLAlchemy() @@ -13,11 +30,14 @@ def create_app(script_info=None): app = Flask(__name__, static_folder='static', static_url_path='') app.config['SQLALCHEMY_DATABASE_URI'] = connection_url app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False + app.config['CELERY_BROKER_URL'] = cfg.CELERY_BROKER_URL + app.config['CELERY_RESULT_BACKEND'] = cfg.CELERY_RESULT_BACKEND db.init_app(app) datasets = load_sql_datasets(replace=False, base_model=db.Model) app.register_blueprint(api, url_prefix='/api') + app.register_blueprint(api_task, url_prefix='/task') app.add_url_rule('/<path:file_relative_path_to_root>', 'serve_page', serve_page, methods=['GET']) @app.route('/', methods=['GET']) diff --git a/megapixels/app/server/tasks/__init__.py b/megapixels/app/server/tasks/__init__.py new file mode 100644 index 00000000..c0db0be5 --- /dev/null +++ b/megapixels/app/server/tasks/__init__.py @@ -0,0 +1,47 @@ +import simplejson as json +from app.settings import app_cfg as cfg +from celery import Celery + +celery = Celery(__name__, backend=cfg.CELERY_RESULT_BACKEND, broker=cfg.CELERY_BROKER_URL) + +from app.server.tasks.sleep import sleep_task +from app.server.tasks.blur import blur_task +from app.server.tasks.demo import demo_task + +def list_active_tasks(): + dropdown = {} + for k,v in task_lookup.items(): + if 'active' not in v or v['active'] is not False: + is_default = 'default' in v and v['default'] is True + task = { + 'name': k, + 'title': v['title'], + 'selected': is_default, + } + dropdown[k] = task + return dropdown + +################################################################### +# Add all valid tasks to this lookup. +# Set 'active': False to disable a task +# Set 'default': True to define the default task + +task_lookup = { + 'sleep': { + 'title': 'Sleep Test', + 'task': sleep_task, + 'active': True, + 'default': True, + }, + 'blur': { + 'title': 'Blur', + 'task': blur_task, + 'active': True, + }, + 'demo': { + 'title': 'Facial processing pipeline', + 'task': demo_task, + 'active': True, + 'default': True, + } +} diff --git a/megapixels/app/server/tasks/blur.py b/megapixels/app/server/tasks/blur.py new file mode 100644 index 00000000..74798cee --- /dev/null +++ b/megapixels/app/server/tasks/blur.py @@ -0,0 +1,81 @@ +import os +import sys +import time +import datetime +import json +from PIL import Image +import cv2 as cv +import numpy as np +from app.utils.im_utils import ensure_np, ensure_pil +from flask import current_app as app + +import app.settings.app_cfg as cfg + +from app.server.tasks import celery + +from celery.utils.log import get_task_logger +log = get_task_logger(__name__) +import imutils + +@celery.task(bind=True) +def blur_task(self, uuid_name, fn): + """Process image and update during""" + log.debug('process_image_task, uuid: {}'.format(uuid_name)) + log.debug('fn: {}'.format(fn)) + + files = [] + + meta = { + 'step': 0, + 'total': 3, + 'message': 'Starting', + 'uuid': uuid_name, + 'data': {}, + } + self.update_state(state='PROCESSING', meta=meta) + + im = Image.open(fn).convert('RGB') + os.remove(fn) + + meta['step'] += 1 + meta['message'] = 'Applying blur' + self.update_state(state='PROCESSING', meta=meta) + + im_np = ensure_np(im) + im_blur = cv.blur(im_np, (5,5), 1.0) + im_blur_pil = ensure_pil(im_blur) + + fn = uuid_name + '_blur.jpg' + fpath = os.path.join(cfg.DIR_SITE_USER_CONTENT, fn) + im_blur_pil.save(fpath, 'JPEG', quality=80) + log.debug('fpath: {}'.format(fpath)) + print('fpath: {}'.format(fpath)) + + # files.append({ + # 'title': 'Blurred image', + # 'fn': render_uri + uuid_name + '_blur.jpg' + # }) + + meta['step'] += 1 + meta['message'] = 'Applying blur' + meta['data']['blur_fn'] = { + 'title': 'Blurred image', + 'url': os.path.join('/user_content/', fn) + } + self.update_state(state='PROCESSING', meta=meta) + time.sleep(3) + + if os.path.exists(fpath): + os.remove(fpath) + + meta['step'] += 1 + meta['message'] = 'Securely deleting user content' + self.update_state(state='PROCESSING', meta=meta) + time.sleep(2) + + log.debug('done!!') + + meta['step'] = meta['total'] + meta['state'] = 'complete' + return meta + diff --git a/megapixels/app/server/tasks/demo.py b/megapixels/app/server/tasks/demo.py new file mode 100644 index 00000000..c27b08b5 --- /dev/null +++ b/megapixels/app/server/tasks/demo.py @@ -0,0 +1,262 @@ + +import app.settings.app_cfg as cfg +from app.server.tasks import celery + +from celery.utils.log import get_task_logger +log = get_task_logger(__name__) + +opt_size = (256, 256,) + +@celery.task(bind=True) +def demo_task(self, uuid_name, fn): + + import sys + import os + from os.path import join + from pathlib import Path + import time + + import numpy as np + import cv2 as cv + import dlib + from PIL import Image + import matplotlib.pyplot as plt + + from app.utils import logger_utils, file_utils, im_utils, display_utils, draw_utils + from app.utils import plot_utils + from app.processors import face_detector, face_landmarks, face_age_gender, face_beauty + # , face_emotion + from app.models.data_store import DataStore + + # TODO add selective testing + opt_gpu = -1 + opt_run_pose = True + opt_run_2d_68 = True + opt_run_3d_68 = True + opt_run_3d_68 = True + + opt_gif_size = (256, 256,) + opt_gif_frames = 15 + + meta = { + 'step': 0, + 'total': 10, + 'message': 'Starting', + 'uuid': uuid_name, + 'data': { 'statistics': {} }, + } + paths = [] + + def step(msg, step=1): + meta['message'] = msg + meta['step'] += step + log.debug('> {}'.format(msg)) + self.update_state(state='PROCESSING', meta=meta) + + def save_image(key, title, data): + fn = '{}_{}.jpg'.format(uuid_name, key) + fpath = os.path.join(cfg.DIR_SITE_USER_CONTENT, fn) + paths.append(fpath) + cv.imwrite(fpath, data) + + meta['data'][key] = { + 'title': title, + 'url': os.path.join('/user_content/', fn), + } + + step('Loading image') + self.update_state(state='PROCESSING', meta=meta) + + # os.path.join('/user_content/', fn) + + # ------------------------------------------------- + # init here + + # load image + im = cv.imread(fn) + im_resized = im_utils.resize(im, width=opt_size[0], height=opt_size[1]) + + # ---------------------------------------------------------------------------- + # detect face + + face_detector_instance = face_detector.DetectorDLIBCNN(gpu=opt_gpu) # -1 for CPU + step('Detecting face') + st = time.time() + bboxes = face_detector_instance.detect(im_resized, largest=True) + bbox = bboxes[0] + dim = im_resized.shape[:2][::-1] + bbox_dim = bbox.to_dim(dim) + if not bbox: + log.error('No face detected') + meta['error'] = 'No face detected' + self.update_state(state='FAILURE', meta=meta) + return meta + else: + log.info(f'Detected face in {(time.time() - st):.2f}s') + + + # ---------------------------------------------------------------------------- + # detect 3D landmarks + + step('Generating 3D Landmarks') + log.info('loading 3D landmark generator files...') + landmark_detector_3d_68 = face_landmarks.FaceAlignment3D_68(gpu=opt_gpu) # -1 for CPU + log.info('generating 3D landmarks...') + st = time.time() + points_3d_68 = landmark_detector_3d_68.landmarks(im_resized, bbox_dim.to_xyxy()) + log.info(f'generated 3D landmarks in {(time.time() - st):.2f}s') + log.info('') + + # draw 3d landmarks + im_landmarks_3d_68 = im_resized.copy() + draw_utils.draw_landmarks3D(im_landmarks_3d_68, points_3d_68) + draw_utils.draw_bbox(im_landmarks_3d_68, bbox_dim) + + save_image('landmarks_3d_68', '3D Landmarks', im_landmarks_3d_68) + + # ---------------------------------------------------------------------------- + # generate 3D GIF animation + + step('Generating GIF Animation') + log.info('generating 3D animation...') + + fn = '{}_{}.gif'.format(uuid_name, '3d') + fp_out = os.path.join(cfg.DIR_SITE_USER_CONTENT, fn) + paths.append(fp_out) + + st = time.time() + plot_utils.generate_3d_landmark_anim(np.array(points_3d_68), fp_out, + size=opt_gif_size, num_frames=opt_gif_frames) + log.info(f'Generated animation in {(time.time() - st):.2f}s') + log.info(f'Saved to: {fp_out}') + log.info('') + + meta['data']['points_3d_68'] = points_3d_68 + meta['data']['points_3d_68'] = { + 'title': '3D Animated GIF', + 'url': os.path.join('/user_content/', fn), + } + + # ---------------------------------------------------------------------------- + # generate 68 point landmarks using dlib + + step('Generating 2D 68PT landmarks') + log.info('initializing face landmarks 68 dlib...') + from app.processors import face_landmarks + landmark_detector_2d_68 = face_landmarks.Dlib2D_68() + log.info('generating 2D 68PT landmarks...') + st = time.time() + points_2d_68 = landmark_detector_2d_68.landmarks(im_resized, bbox_dim) + log.info(f'generated 2D 68PT face landmarks in {(time.time() - st):.2f}s') + log.info('') + + # draw 2d landmarks + im_landmarks_2d_68 = im_resized.copy() + draw_utils.draw_landmarks2D(im_landmarks_2d_68, points_2d_68) + draw_utils.draw_bbox(im_landmarks_2d_68, bbox_dim) + save_image('landmarks_2d_68', '2D Landmarks', im_landmarks_2d_68) + + # ---------------------------------------------------------------------------- + # generate pose from 68 point 2D landmarks + + if opt_run_pose: + step('Generating pose') + log.info('initialize pose...') + from app.processors import face_pose + pose_detector = face_pose.FacePoseDLIB() + log.info('generating pose...') + st = time.time() + pose_data = pose_detector.pose(points_2d_68, dim) + log.info(f'generated pose {(time.time() - st):.2f}s') + log.info('') + + im_pose = im_resized.copy() + draw_utils.draw_pose(im_pose, pose_data['point_nose'], pose_data['points']) + draw_utils.draw_degrees(im_pose, pose_data) + save_image('pose', 'Pose', im_pose) + + # ---------------------------------------------------------------------------- + # age + + # real + step('Running age predictor') + age_real_predictor = face_age_gender.FaceAgeReal() + st = time.time() + age_real = age_real_predictor.predict(im_resized, bbox_dim) + log.info(f'age real took: {(time.time()-st)/1000:.5f}s') + meta['data']['statistics']['age_real'] = f'{(age_real):.2f}' + + # apparent + age_apparent_predictor = face_age_gender.FaceAgeApparent() + st = time.time() + age_apparent = age_apparent_predictor.predict(im_resized, bbox_dim) + log.info(f'age apparent took: {(time.time()-st)/1000:.5f}s') + meta['data']['statistics']['age_apparent'] = f'{(age_apparent):.2f}' + + # gender + step('Running gender predictor') + gender_predictor = face_age_gender.FaceGender() + st = time.time() + gender = gender_predictor.predict(im_resized, bbox_dim) + log.info(f'gender took: {(time.time()-st)/1000:.5f}s') + meta['data']['statistics']['gender'] = f"M: {gender['m']:.2f}, F: {gender['f']:.2f}" + + # # ---------------------------------------------------------------------------- + # # emotion + + # emotion_predictor = face_emotion.FaceEmotion(gpu=opt_gpu) + # emotion_score = emotion_predictor.emotion(im_resized, bbox_dim) + # log.info(f'emotion score: {(100*emotion_score):.2f}') + + # im_emotion = im_resized.copy() + # draw_utils.draw_bbox(im_emotion, bbox_dim) + # txt = f'emotion score: {(100*emotion_score):.2f}' + # draw_utils.draw_text(im_emotion, bbox_dim.pt_tl, txt) + # save_image('emotion', 'Emotion', im_emotion) + + + # ---------------------------------------------------------------------------- + # beauty + + # TODO fix Keras CPU/GPU device selection issue + # NB: GPU visibility issues with dlib/keras + # Wrap this with cuda toggle and run before init dlib GPU + + step('Running beauty predictor') + device_cur = os.getenv('CUDA_VISIBLE_DEVICES', '') + os.environ['CUDA_VISIBLE_DEVICES'] = '' + beauty_predictor = face_beauty.FaceBeauty() + os.environ['CUDA_VISIBLE_DEVICES'] = device_cur + + beauty_score = beauty_predictor.beauty(im_resized, bbox_dim) + log.info(f'beauty score: {(100*beauty_score):.2f}') + + # # draw 2d landmarks + # im_beauty = im_resized.copy() + # draw_utils.draw_bbox(im_beauty, bbox_dim) + # txt = f'Beauty score: {(100*beauty_score):.2f}' + # draw_utils.draw_text(im_beauty, bbox_dim.pt_tl, txt) + # save_image('beauty', 'Beauty', im_beauty) + meta['data']['statistics']['beauty'] = f'{(100*beauty_score):.2f}' + + step('Done') + + # # 3DDFA + # self.log.debug('Add depth') + # self.log.debug('Add pncc') + + # # TODO + # self.log.debug('Add 3D face model') + # self.log.debug('Add face texture flat') + # self.log.debug('Add ethnicity') + + log.debug('done!!') + + time.sleep(3) + for path in paths: + if os.path.exists(path): + os.remove(path) + + meta['step'] = meta['total'] + meta['state'] = 'SUCCESS' + return meta diff --git a/megapixels/app/server/tasks/sleep.py b/megapixels/app/server/tasks/sleep.py new file mode 100644 index 00000000..fa40b0e9 --- /dev/null +++ b/megapixels/app/server/tasks/sleep.py @@ -0,0 +1,38 @@ +import time + +# from .. import basemodels +# celery = basemodels.celery + +from celery.utils.log import get_task_logger +celery_logger = get_task_logger(__name__) + +from app.server.tasks import celery + +import imutils + +@celery.task(bind=True) +def sleep_task(self, uuid_name): + celery_logger.debug('sleep_task'.format(uuid_name)) + msgs = [ + {'msg':'Uploaded OK','time':.1}, + {'msg':'Segmenting Image...','time':2}, + {'msg':'Found: Person, Horse','time':1}, + {'msg':'Creating Pix2Pix','time':2} + ] + for i,m in enumerate(msgs): + percent = int(float(i)/float(len(msgs))*100.0) + self.update_state( + state = 'processing', + meta = { + 'percent': percent, + 'message': m['msg'], + 'uuid': uuid_name + }) + celery_logger.debug(m['msg']) + time.sleep(m['time']) + + return { + 'percent': 100, + 'state': 'complete', + 'uuid': uuid_name + } diff --git a/megapixels/app/settings/app_cfg.py b/megapixels/app/settings/app_cfg.py index fde9fed7..14e2493c 100644 --- a/megapixels/app/settings/app_cfg.py +++ b/megapixels/app/settings/app_cfg.py @@ -150,3 +150,10 @@ S3_DATASETS_PATH = "v1" # datasets is already in the filename DIR_SITE_PUBLIC = "../site/public" DIR_SITE_CONTENT = "../site/content" DIR_SITE_TEMPLATES = "../site/templates" +DIR_SITE_USER_CONTENT = "../site/public/user_content" + +# ----------------------------------------------------------------------------- +# Celery +# ----------------------------------------------------------------------------- +CELERY_BROKER_URL = 'redis://localhost:6379/0' +CELERY_RESULT_BACKEND = 'redis://localhost:6379/0' diff --git a/megapixels/app/utils/im_utils.py b/megapixels/app/utils/im_utils.py index e882c67f..d36c1c32 100644 --- a/megapixels/app/utils/im_utils.py +++ b/megapixels/app/utils/im_utils.py @@ -19,7 +19,19 @@ from torch.autograd import Variable from sklearn.metrics.pairwise import cosine_similarity import datetime +def ensure_pil(im): + """Ensure image is Pillow format""" + try: + im.verify() + return im + except: + return Image.fromarray(im.astype('uint8'), 'RGB') +def ensure_np(im): + """Ensure image is numpy array""" + if type(im) == np.ndarray: + return im + return np.asarray(im, np.uint8) def num_channels(im): '''Returns number of channels in numpy.ndarray image''' |