diff options
| author | Jules Laplace <julescarbon@gmail.com> | 2019-01-17 16:46:02 +0100 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2019-01-17 16:46:02 +0100 |
| commit | 6595e3d61fb445fc06c835c4f72d4c534524ae33 (patch) | |
| tree | 8b8632f651e1bd31a2d22e925640f276a5f1e6cb /megapixels/app/server | |
| parent | 6a59583ff2f13791e3d7e8a69b62dc4bc424c9eb (diff) | |
fix api
Diffstat (limited to 'megapixels/app/server')
| -rw-r--r-- | megapixels/app/server/api.py | 17 |
1 files changed, 10 insertions, 7 deletions
diff --git a/megapixels/app/server/api.py b/megapixels/app/server/api.py index 4f564710..81fffdd8 100644 --- a/megapixels/app/server/api.py +++ b/megapixels/app/server/api.py @@ -7,7 +7,7 @@ import operator from flask import Blueprint, request, jsonify from PIL import Image # todo: try to remove PIL dependency -from app.processors.face_extractor import ExtractorDLIB +from app.processors import face_extractor 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 @@ -67,27 +67,30 @@ def upload(dataset_name): # get detection as BBox object bboxes = detector.detect(im_np, largest=True, pyramids=2) + if not bboxes or not len(bboxes): return jsonify({ 'error': 'bbox' }) - bbox = bboxes[0] - if not bbox: + + bbox_norm = bboxes[0] + if not bbox_norm: return jsonify({ 'error': 'bbox' }) dim = im_np.shape[:2][::-1] - bbox = bbox.to_dim(dim) # convert back to real dimensions + bbox_dim = bbox_norm.to_dim(dim) + # bbox = bbox.to_dim(dim) # convert back to real dimensions # print("got bbox") - if not bbox: + if not bbox_dim: return jsonify({ 'error': 'bbox' }) # extract 128-D vector extractor = face_extractor.ExtractorDLIB() - vec = extractor.extract(im, bbox_norm) # NB use norm, not bbox_dim + vec = extractor.extract(im_np, bbox_norm) # NB use norm, not bbox_dim # recognition = face_recognition.RecognitionDLIB(gpu=-1) # vec = recognition.vec(im_np, bbox) query = np.array([ vec ]).astype('float32') @@ -124,7 +127,7 @@ def upload(dataset_name): query = { 'timing': round(time.time() - start, 3), - 'bbox': str(bbox), + 'bbox': str(bbox_norm), } # print(results) return jsonify({ |
