1 files changed, 152 insertions, 0 deletions
diff --git a/megapixels/app/server/api.py b/megapixels/app/server/api.py
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+import os
+import re
+import time
+import dlib
+import numpy as np
+from flask import Blueprint, request, jsonify
+from PIL import Image  # todo: try to remove PIL dependency
+
+from app.processors import face_recognition
+from app.processors import face_detector
+from app.processors.faiss import load_faiss_databases
+from app.models.sql_factory import load_sql_datasets, list_datasets, get_dataset, get_table
+from app.utils.im_utils import pil2np
+
+sanitize_re = re.compile('[\W]+')
+valid_exts = ['.gif', '.jpg', '.jpeg', '.png']
+
+LIMIT = 9
+THRESHOLD = 0.3
+
+api = Blueprint('api', __name__)
+
+faiss_datasets = load_faiss_databases()
+
+@api.route('/')
+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"""
+  dataset = get_dataset(dataset_name)
+  if dataset:
+    return jsonify(dataset.describe())
+  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"""
+  start = time.time()
+  dataset = get_dataset(dataset_name)
+  if dataset_name not in faiss_datasets:
+    return jsonify({
+      'error': 'invalid dataset'  
+    })
+  faiss_dataset = faiss_datasets[dataset_name]
+  file = request.files['query_img']
+  fn = file.filename
+  if fn.endswith('blob'):
+    fn = 'filename.jpg'
+
+  basename, ext = os.path.splitext(fn)
+  # print("got {}, type {}".format(basename, ext))
+  if ext.lower() not in valid_exts:
+    return jsonify({ 'error': 'not an image' })
+
+  im = Image.open(file.stream).convert('RGB')
+  im_np = pil2np(im)
+
+  # Face detection
+  detector = face_detector.DetectorDLIBHOG()
+
+  # get detection as BBox object
+  bboxes = detector.detect(im_np, largest=True)
+  if not bboxes or not len(bboxes):
+    return jsonify({
+      'error': 'bbox'
+    })
+  bbox = bboxes[0]
+  if not bbox:
+    return jsonify({
+      'error': 'bbox'
+    })
+
+  dim = im_np.shape[:2][::-1]
+  bbox = bbox.to_dim(dim)  # convert back to real dimensions
+  # print("got bbox")
+  if not bbox:
+    return jsonify({
+      'error': 'bbox'
+    })
+
+  # extract 128-D vector
+  recognition = face_recognition.RecognitionDLIB(gpu=-1)
+  vec = recognition.vec(im_np, bbox)
+  query = np.array([ vec ]).astype('float32')
+  
+  # query FAISS
+  distances, indexes = faiss_dataset.search(query, LIMIT)
+
+  if len(indexes) == 0 or len(indexes[0]) == 0:
+    return jsonify({
+      'error': 'nomatch'
+    })
+
+  # get the results for this single query...
+  distances = distances[0]
+  indexes = indexes[0]
+
+  dists = []
+  ids = []
+  for _d, _i in zip(distances, indexes):
+    if _d <= THRESHOLD:
+      dists.append(round(float(_d), 2))
+      ids.append(_i+1)
+
+  results = [ dataset.get_identity(int(_i)) for _i in ids ]
+
+  # print(distances)
+  # print(ids)
+
+  # 'bbox': str(bboxes[0]),
+  # 'bbox_dim': str(bbox),
+  # print(bboxes[0])
+  # print(bbox)
+
+  query = {
+    'timing': round(time.time() - start, 3),
+    'bbox': str(bbox),
+  }
+  # print(results)
+  return jsonify({
+    'query': query,
+    'results': results,
+    'distances': dists,
+  })
+
+
+@api.route('/dataset/<dataset_name>/name', methods=['GET','POST'])
+def name_lookup(dataset_name):
+  """Find a name in the dataset"""
+  start = time.time()
+  dataset = get_dataset(dataset_name)
+
+  q = request.args.get('q')
+  # print(q)
+
+  query = {
+    'q': q,
+    'timing': time.time() - start,
+  }
+  results = dataset.search_name(q + '%') if q else None
+  
+  # print(results)
+  return jsonify({
+    'query': query,
+    'results': results,
+  })