From 87d9ca49f1ec2df59c0999a30cff958a3537b985 Mon Sep 17 00:00:00 2001
From: Kai Chen <chenkaidev@gmail.com>
Date: Thu, 8 Aug 2019 16:39:15 +0800
Subject: [PATCH] add webcam demo (#1150)
---
GETTING_STARTED.md | 17 ++++++++++++++++-
tools/webcam_demo.py | 38 ++++++++++++++++++++++++++++++++++++++
2 files changed, 54 insertions(+), 1 deletion(-)
create mode 100644 tools/webcam_demo.py
diff --git a/GETTING_STARTED.md b/GETTING_STARTED.md
index 9e9c6f0..728cbbe 100644
--- a/GETTING_STARTED.md
+++ b/GETTING_STARTED.md
@@ -57,7 +57,22 @@ python tools/test.py configs/mask_rcnn_r50_fpn_1x.py \
8 --out results.pkl --eval bbox segm
```
-### High-level APIs for testing images.
+### Webcam demo
+
+We provide a webcam demo to illustrate the results.
+
+```shell
+python tools/webcam_demo.py ${CONFIG_FILE} ${CHECKPOINT_FILE} [--device ${GPU_ID}] [--camera-id ${CAMERA-ID}] [--score-thr ${CAMERA-ID}]
+```
+
+Examples:
+
+```shell
+python tools/webcam_demo.py configs/faster_rcnn_r50_fpn_1x.py \
+ checkpoints/faster_rcnn_r50_fpn_1x_20181010-3d1b3351.pth
+```
+
+### High-level APIs for testing images
Here is an example of building the model and test given images.
diff --git a/tools/webcam_demo.py b/tools/webcam_demo.py
new file mode 100644
index 0000000..c1ef27a
--- /dev/null
+++ b/tools/webcam_demo.py
@@ -0,0 +1,38 @@
+import argparse
+
+import cv2
+import torch
+
+from mmdet.apis import inference_detector, init_detector, show_result
+
+
+def parse_args():
+ parser = argparse.ArgumentParser(description='MMDetection webcam demo')
+ parser.add_argument('config', help='test config file path')
+ parser.add_argument('checkpoint', help='checkpoint file')
+ parser.add_argument('--device', type=int, default=0, help='CUDA device id')
+ parser.add_argument(
+ '--camera-id', type=int, default=0, help='camera device id')
+ parser.add_argument(
+ '--score-thr', type=float, default=0.5, help='bbox score threshold')
+ args = parser.parse_args()
+ return args
+
+
+def main():
+ args = parse_args()
+
+ model = init_detector(
+ args.config, args.checkpoint, device=torch.device('cuda', args.device))
+
+ camera = cv2.VideoCapture(args.camera_id)
+
+ while True:
+ ret_val, img = camera.read()
+ result = inference_detector(model, img)
+ show_result(
+ img, result, model.CLASSES, score_thr=args.score_thr, wait_time=1)
+
+
+if __name__ == '__main__':
+ main()
--
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