Object_Detection: NanoDet (GSOC)

[Sidd1609]

Updated files for object detection using YOLOX,
files uploaded for review:

• Model files (.onnx format FP16)
• Model: Nanodet-plus-m-1.5x-416
• README
• LICENSE (Apache 2.0)
• demo.py (with image and webcam inference options)
• NanoDet.py (class NanoDet)
• examples (test_data: test images, results: inferred results)
• COCO class names (coco.names)

COMPLETED:

• Model upload
• demo file
• NanoDet file
• Example inference (image and webcam)

TO DO:

• Model quantization

[fengyuentau]

This PR is for NanoDet, so please remove the object_detection_yolox directory.

[Sidd1609]

removed yolox directory

[Sidd1609]

Yes, resolving the changes

…

On Sun, Sep 4, 2022 at 7:38 AM Yuantao Feng ***@***.***> wrote: ***@***.**** commented on this pull request. ------------------------------ In models/object_detection_nanodet/NanodetPlus.py <#87 (comment)>: > + with open('coco.names', 'rt') as f: + self.classes = f.read().rstrip('\n').split('\n') Lets keep all classes here in this file like this <https://github.com/open-mmlab/mmdetection/blob/df28da98926bc410e16bed1e9fc7d425d9a89495/mmdet/datasets/coco.py#L25-L38> ------------------------------ In models/object_detection_nanodet/NanodetPlus.py <#87 (comment)>: > + top, left, newh, neww = 0, 0, self.image_shape[0], self.image_shape[1] + if keep_ratio and srcimg.shape[0] != srcimg.shape[1]: + hw_scale = srcimg.shape[0] / srcimg.shape[1] + if hw_scale > 1: + newh, neww = self.image_shape[0], int(self.image_shape[1] / hw_scale) + img = cv2.resize(srcimg, (neww, newh), interpolation=cv2.INTER_AREA) + left = int((self.image_shape[1] - neww) * 0.5) + img = cv2.copyMakeBorder(img, 0, 0, left, self.image_shape[1] - neww - left, cv2.BORDER_CONSTANT, + value=0) # add border + else: + newh, neww = int(self.image_shape[0] * hw_scale), self.image_shape[1] + img = cv2.resize(srcimg, (neww, newh), interpolation=cv2.INTER_AREA) + top = int((self.image_shape[0] - newh) * 0.5) + img = cv2.copyMakeBorder(img, top, self.image_shape[0] - newh - top, 0, 0, cv2.BORDER_CONSTANT, value=0) + else: + img = cv2.resize(srcimg, self.image_shape, interpolation=cv2.INTER_AREA) + + blob = self.pre_process(img) Can we reuse the code from yolox for letterbox preprocessing? ------------------------------ In models/object_detection_nanodet/NanodetPlus.py <#87 (comment)>: > + value=0) # add border + else: + newh, neww = int(self.image_shape[0] * hw_scale), self.image_shape[1] + img = cv2.resize(srcimg, (neww, newh), interpolation=cv2.INTER_AREA) + top = int((self.image_shape[0] - newh) * 0.5) + img = cv2.copyMakeBorder(img, top, self.image_shape[0] - newh - top, 0, 0, cv2.BORDER_CONSTANT, value=0) + else: + img = cv2.resize(srcimg, self.image_shape, interpolation=cv2.INTER_AREA) + + blob = self.pre_process(img) + self.net.setInput(blob) + outs = self.net.forward(self.net.getUnconnectedOutLayersNames()) + det_bboxes, det_conf, det_classid = self.post_process(outs) + ratioh,ratiow = srcimg.shape[0]/newh,srcimg.shape[1]/neww + + return left, top, ratioh, ratiow, det_bboxes, det_conf, det_classid I propose to have the same formatting of results of yolox. ------------------------------ In models/object_detection_nanodet/coco.names <#87 (comment)>: > @@ -0,0 +1,80 @@ +person This file is not needed if we keep these classes in the wrapper class. ------------------------------ In models/object_detection_nanodet/demo.py <#87 (comment)>: > + if(Video_save): + clip = moviepy.video.io.ImageSequenceClip.ImageSequenceClip(frame_list, fps=fps) + clip.write_videofile('Webcam_result.mp4') Use VideoWriter instead. — Reply to this email directly, view it on GitHub <#87 (review)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ALTC7V6AFWSL5FZ72IKDEKDV4QAANANCNFSM57AGTIAA> . You are receiving this because you authored the thread.Message ID: ***@***.***>

[fengyuentau]

@Sidd1609 could you squash commits into one? I am going to work on this pr and merge it.

[Sidd1609]

Changes have been made for nanodet And yolox commits have been updated in separate branch

…

On Fri, Oct 21, 2022 at 12:37 PM Yuantao Feng ***@***.***> wrote: @Sidd1609 <https://github.com/Sidd1609> could you squash commits into one? I am going to work on this pr and merge it. — Reply to this email directly, view it on GitHub <#87 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ALTC7V3SWF7K6DDP2F5W6OTWEI6MHANCNFSM57AGTIAA> . You are receiving this because you were mentioned.Message ID: ***@***.***>

[fengyuentau]

close in favor of #103