From 1e176a01ac18af35894123901059f6f28a962d29 Mon Sep 17 00:00:00 2001
From: Aymeric Chaumont <aymeric.chaumont@student-cs.fr>
Date: Wed, 20 Jul 2022 14:22:42 +0200
Subject: [PATCH] minor fixes
---
backend/video_capture.py | 11 ++++-------
1 file changed, 4 insertions(+), 7 deletions(-)
diff --git a/backend/video_capture.py b/backend/video_capture.py
index a0d537c..7195181 100644
--- a/backend/video_capture.py
+++ b/backend/video_capture.py
@@ -23,8 +23,7 @@ async def handle_cameras():
while True:
- start_timestamp = time.time()
- current_date = datetime.fromtimestamp(start_timestamp)
+ current_date = datetime.now()
weekday, current_time = current_date.weekday(), current_date.time()
for restaurant in restaurants:
@@ -54,9 +53,7 @@ async def handle_cameras():
np.array(
[treated_img]))),
axis=0)
- pre_pred = time.time()
pred_map = np.squeeze(model.predict(input_image, verbose=0))
- print(time.time() - pre_pred)
count_prediction += np.sum(pred_map)
for caisse in camera["caisses"]:
if np.sum(pred_map[caisse["x1"] // 2:caisse["x2"] // 2, caisse["y1"] // 2:caisse["y2"] // 2]) > 0.5:
@@ -65,11 +62,11 @@ async def handle_cameras():
cams_working = False
cap.release()
- if cams_working:
+ if cams_working and open_checkouts:
waiting_time = timedelta(
seconds=restaurant['b_factor'] +
int(count_prediction *
- restaurant['a_factor'] / max(open_checkouts, 1)))
+ restaurant['a_factor'] / open_checkouts))
db_record = models.Records(
place=restaurant['restaurant'],
date=current_date,
@@ -78,4 +75,4 @@ async def handle_cameras():
db.add(db_record)
db.commit()
await manager.broadcast(json.dumps({"type": "data"}))
- time.sleep(60 - time.time() + start_timestamp)
+ time.sleep(60 - (datetime.now() - current_date).total_seconds())
--
GitLab