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Fix SDK backend (#844)

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Chen Xin 2022-08-02 11:49:25 +08:00 committed by GitHub
parent a15365e93f
commit e12dfddc26
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8 changed files with 11 additions and 13 deletions
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3
mmdeploy/codebase/mmcls/deploy/classification_model.py
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@ -139,8 +139,7 @@ class SDKEnd2EndModel(End2EndModel):
list: A list contains predictions.
"""
pred = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])[0]
pred = self.wrapper.invoke(img[0].contiguous().detach().cpu().numpy())
pred = np.array(pred, dtype=np.float32)
return pred[np.argsort(pred[:, 0])][np.newaxis, :, 1]

2
mmdeploy/codebase/mmdet/deploy/object_detection_model.py
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@ -637,7 +637,7 @@ class SDKEnd2EndModel(End2EndModel):
list: A list contains predictions.
"""
dets, labels, masks = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])[0]
img[0].contiguous().detach().cpu().numpy())
det_results = bbox2result(dets[np.newaxis, ...], labels[np.newaxis,
...],
len(self.CLASSES))

2
mmdeploy/codebase/mmedit/deploy/super_resolution_model.py
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@ -223,7 +223,7 @@ class SDKEnd2EndModel(End2EndModel):
list | dict: High resolution image or a evaluation results.
"""
img = tensor2img(lq)
output = self.wrapper.invoke([img])[0]
output = self.wrapper.invoke(img)
if test_mode:
output = torch.from_numpy(output)
output = output.permute(2, 0, 1)

2
mmdeploy/codebase/mmocr/deploy/text_detection_model.py
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@ -169,7 +169,7 @@ class SDKEnd2EndModel(End2EndModel):
list: A list contains predictions.
"""
boundaries = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])[0]
img[0].contiguous().detach().cpu().numpy())
boundaries = [list(x) for x in boundaries]
return [
dict(

6
mmdeploy/codebase/mmocr/deploy/text_recognition_model.py
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@ -181,9 +181,9 @@ class SDKEnd2EndModel(End2EndModel):
Returns:
list[str]: Text label result of each image.
"""
results = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])
results = [dict(text=text, score=score) for text, score in results]
text, score = self.wrapper.invoke(
img[0].contiguous().detach().cpu().numpy())
results = [dict(text=text, score=score)]
return results

4
mmdeploy/codebase/mmpose/deploy/pose_detection_model.py
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@ -218,8 +218,8 @@ class SDKEnd2EndModel(End2EndModel):
image_paths.append(img_meta['image_file'])
bbox_ids.append(img_meta['bbox_id'])
pred = self.wrapper.handle(
[img[0].contiguous().detach().cpu().numpy()], [sdk_boxes])[0]
pred = self.wrapper.handle(img[0].contiguous().detach().cpu().numpy(),
sdk_boxes)
result = dict(
preds=pred,

2
mmdeploy/codebase/mmrotate/deploy/rotated_detection_model.py
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@ -212,7 +212,7 @@ class SDKEnd2EndModel(End2EndModel):
"""
results = []
dets, labels = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])[0]
img[0].contiguous().detach().cpu().numpy())
dets_results = [dets[labels == i, :] for i in range(len(self.CLASSES))]
results.append(dets_results)

3
mmdeploy/codebase/mmseg/deploy/segmentation_model.py
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@ -166,8 +166,7 @@ class SDKEnd2EndModel(End2EndModel):
Returns:
list: A list contains predictions.
"""
masks = self.wrapper.invoke(
[img[0].contiguous().detach().cpu().numpy()])[0]
masks = self.wrapper.invoke(img[0].contiguous().detach().cpu().numpy())
return masks