Implement API for predictions

code/jetson-deployment/server.py

@@ -1,12 +1,22 @@
+import argparse
+import logging
 import atexit
-import jetson.utils
+import os
+
+import cv2
+import json
+import base64
+import datetime
+from dateutil.parser import parse
+from copy import deepcopy
 
 from flask import Flask
 from apscheduler.schedulers.background import BackgroundScheduler
 
 from multiprocessing import Manager
 
-from code.evaluation.detection import detect
+from evaluation.detection import detect
+from utils.manipulations import draw_boxes
 
 app = Flask(__name__)
 scheduler = BackgroundScheduler(daemon=True)
@@ -14,39 +24,130 @@ manager = Manager()
 pred = manager.dict()
 
 
-@scheduler.task('interval', id='get_pred', minutes=30, misfire_grace_time=900)
 def get_pred():
-    img = take_image('./current_image.jpg')
+    tmp = deepcopy(pred)
-    print('Job 1 executed')
+    take_image()
+    logging.debug('Starting image classification')
+    preds = detect('current.jpg', '../weights/yolo.onnx',
+                   '../weights/resnet.onnx')
+    logging.debug('Finished image classification: %s', preds)
+    logging.debug('Reading current.jpg for drawing bounding boxes')
+    current = cv2.imread('current.jpg')
+    logging.debug('Drawing bounding boxes on current.jpg')
+    bbox_img = draw_boxes(
+        current, preds[['xmin', 'ymin', 'xmax',
+                        'ymax']].itertuples(index=False, name=None))
+    logging.debug(
+        'Finished drawing bounding boxes. Saving to current_bbox.jpg ...')
+    cv2.imwrite('current_bbox.jpg', bbox_img)
+
+    # Clear superfluous bboxes if less detected
+    # if len(preds) < len(pred):
+    #     logging.debug(
+    #         'Current round contains less bboxes than previous round: old: %s\nnew: %s',
+    #         json.dumps(preds.copy()), json.dumps(pred.copy()))
+    #     for key in pred:
+    #         if key not in preds:
+    #             pred.pop(key)
+
+    pred.clear()
+    for idx, row in preds.iterrows():
+        new = []
+        state = int(round(float(row['cls_conf']) / 10, 0))
+        new.append(state)
+        new.append(datetime.datetime.now(datetime.timezone.utc).isoformat())
+        try:
+            pred[str(idx)] = tmp[str(idx)]
+        except KeyError:
+            pass
+
+        try:
+            if tmp[idx][2] == -1 and state > 3:
+                logging.debug(
+                    'State is worse than 3 for the first time: %s ... populating third field',
+                    str(state))
+                new.append(
+                    datetime.datetime.now(datetime.timezone.utc).isoformat())
+            elif tmp[idx][2] != -1 and state <= 3:
+                logging.debug(
+                    'State changed from worse than 3 to better than 3')
+                new.append(-1)
+            elif tmp[idx][2] != -1 and state > 3:
+                logging.debug('State is still worse than 3')
+                new.append(tmp[idx][2])
+        except:
+            logging.debug('Third key does not exist')
+            if state > 3:
+                logging.debug(
+                    'State is worse than 3. Populating third field with timestamp'
+                )
+                new.append(
+                    datetime.datetime.now(datetime.timezone.utc).isoformat())
+            else:
+                logging.debug(
+                    'State is better than 3. Populating third field with -1')
+                new.append(-1)
+
+        pred[idx] = new
+
+    bbox_img_b64 = base64.b64encode(cv2.imencode('.jpg', bbox_img)[1]).decode()
+    pred['image'] = bbox_img_b64
+    logging.debug('Saved bbox_img to json')
 
 
-def take_image(img_path: str):
+def take_image():
     """Take an image with the webcam and save it to the specified
     path.
 
     :param str img_path: path image should be saved to
     :returns: captured image
-
     """
-    input = jetson.utils.videoSource('csi://0')
+    capture_path = os.path.join('.', 'image-capture', 'capture')
-    output = jetson.utils.videoOutput(img_path)
+    if os.path.isfile(capture_path) and os.access(capture_path, os.X_OK):
-    img = input.Capture()
+        logging.debug('Starting image capture')
-    output.Render(img)
+        os.system('./image-capture/capture')
-    return img
+        logging.debug('Finished image capture')
-
+    else:
+        logging.critical(
+            'Image capture binary is not at path %s. Shutting down server...',
+            capture_path)
+        app.terminate()
 
 
 @app.route('/')
 def index():
-    # TODO: call script and save initial image with bounding boxes
+    copy = pred.copy()
-    # TODO: get predictions and output them in JSON via API
+    for key, value in copy.items():
-    # TODO: periodically get image from webcam and go to beginning
+        if key == 'image':
-    # TODO: JSON format: [Nr, state (1-10), timestamp, time since below 3]
+            continue
-    return 'Server works'
+        if value[2] != -1:
+            logging.debug('value: %s', value)
+            # Calc difference to now
+            time_below_thresh = parse(value[2])
+            now = datetime.datetime.now(datetime.timezone.utc)
+            delta = now - time_below_thresh
+            value[2] = str(delta)
+    return json.dumps(copy)
 
 
 if __name__ == '__main__':
-    scheduler.add_job(func=get_pred, trigger='interval', minutes=30)
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        '--log',
+        type=str,
+        help='log level (debug, info, warning, error, critical)',
+        default='warning')
+    opt = parser.parse_args()
+    numeric_level = getattr(logging, opt.log.upper(), None)
+    logging.basicConfig(format='%(levelname)s::%(asctime)s::%(message)s',
+                        datefmt='%Y-%m-%dT%H:%M:%S',
+                        level=numeric_level)
+
+    scheduler.add_job(func=get_pred,
+                      trigger='interval',
+                      minutes=2,
+                      next_run_time=datetime.datetime.now())
     scheduler.start()
-    atexit.register(scheduler.shutdown())
+    atexit.register(scheduler.shutdown)
+
     app.run()

code/utils/manipulations.py

@@ -5,6 +5,7 @@ def draw_boxes(image, bboxes):
     img = image.copy()
     for idx, bbox in enumerate(bboxes):
         xmin, ymin, xmax, ymax = bbox
+        xmin, ymin, xmax, ymax = int(xmin), int(ymin), int(xmax), int(ymax)
         # Draw bounding box and number on original image
         img = cv2.rectangle(img, (xmin, ymin), (xmax, ymax), (0, 255, 0), 2)
         img = cv2.putText(img, str(idx), (xmin + 5, ymin + 25),