Comments (4)
If you only want to detect objects, without segmentation, you can use our implementation of retinanet:
https://github.com/fizyr/keras-retinanet
from keras-maskrcnn.
First of all, thank you for your timely reply.I have tried retinanet to detecte the car and the shop logos. Among them, the vehicle detection effect is very good, but the brand detection is not satisfactory. After debugging the parameters, the test score reaches the bottleneck area, so we are looking for a new scheme. I am looking forward to your valuable advice. Thank you!
from keras-maskrcnn.
Let's move this discussion to the keras-retinanet slack channel.
from keras-maskrcnn.
Okay.
from keras-maskrcnn.
Related Issues (20)
- Class agnostic mask-RCNN HOT 1
- Access regression, classification and masks submodel outputs HOT 1
- which layer to extract feature image as image embedding HOT 2
- Off-by-one rounding error in OID mask resizing HOT 3
- Convert resnet50_coco_v0.2.0.h5 to tensorflow serving
- Is it possible to calculate the Dice loss ? HOT 1
- TypeError: Unexpected keyword argument passed to optimizer: learning_rate
- how to train on TPU? should I migrate keras to tf.keras?
- ModuleNotFoundError: No module named 'keras_retinanet.utils.gpu HOT 5
- AttributeError: 'tuple' object has no attribute 'layer' HOT 1
- Training error regarding retinanet HOT 2
- Config file HOT 1
- Difference between weights and snapshots in your implementation (also w/o freeze model argument) HOT 2
- AttributeError: module 'tensorflow' has no attribute 'config' HOT 1
- No mask output
- Is there any chance to have Keras_MaskRCNN in Tensorflow 2 and compatible with Keras_Retinanet ? HOT 1
- Installation fail HOT 1
- the dimension of inference result was 3 HOT 4
- in detection box[2] < box[0] HOT 3
- Weird losses behaviour HOT 17
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