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Traceback (most recent call last):
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 2095, in __call__
return self.wsgi_app(environ, start_response)
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 2080, in wsgi_app
response = self.handle_exception(e)
File "/usr/local/lib/python3.7/site-packages/flask_restful/__init__.py", line 271, in error_router
return original_handler(e)
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 2077, in wsgi_app
response = self.full_dispatch_request()
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1525, in full_dispatch_request
rv = self.handle_user_exception(e)
File "/usr/local/lib/python3.7/site-packages/flask_restful/__init__.py", line 271, in error_router
return original_handler(e)
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1523, in full_dispatch_request
rv = self.dispatch_request()
File "/usr/local/lib/python3.7/site-packages/flask/app.py", line 1509, in dispatch_request
return self.ensure_sync(self.view_functions[rule.endpoint])(**req.view_args)
File "/usr/local/lib/python3.7/site-packages/flask_restful/__init__.py", line 467, in wrapper
resp = resource(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/flask/views.py", line 84, in view
return current_app.ensure_sync(self.dispatch_request)(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/flask_restful/__init__.py", line 582, in dispatch_request
resp = meth(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/flask_apispec/annotations.py", line 122, in wrapped
return wrapper(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/flask_apispec/wrapper.py", line 29, in __call__
response = self.call_view(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/flask_apispec/wrapper.py", line 52, in call_view
return self.func(*args, **kwargs)
File "/app/crop_doctor/resource.py", line 90, in post
cropped_image_path, Is_detected , before_crop_image_path, object_detection_label = object_detection(image_path,file_name)
File "/app/crop_doctor/crop_object_detection.py", line 37, in object_detection
prediction = model_type.end2end_detect(image, valid_tfms, model, class_map=class_map, detection_threshold=0.5)
File "/usr/local/lib/python3.7/site-packages/icevision/imports.py", line 88, in __call__
return self._partial(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/icevision/models/inference.py", line 65, in _end2end_detect
pred = predict_fn(model, infer_ds, detection_threshold=detection_threshold)[0]
File "/usr/local/lib/python3.7/site-packages/icevision/models/ross/efficientdet/prediction.py", line 58, in predict
device=device,
File "/usr/local/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "/usr/local/lib/python3.7/site-packages/icevision/models/ross/efficientdet/prediction.py", line 31, in _predict_batch
raw_preds = bench(x=imgs, img_info=img_info)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/bench.py", line 92, in forward
class_out, box_out = self.model(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 617, in forward
x = self.fpn(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 360, in forward
x = self.cell(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 34, in forward
x = module(x)
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 295, in forward
x.append(fn(x))
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 254, in forward
return self.after_combine(self.combine(x))
File "/usr/local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/usr/local/lib/python3.7/site-packages/effdet/efficientdet.py", line 235, in forward
[(nodes[i] * edge_weights[i]) / (weights_sum + 0.0001) for i in range(len(nodes))], dim=-1)
RuntimeError: stack expects each tensor to be equal size, but got [1, 64, 15, 9] at entry 0 and [1, 64, 16, 10] at entry 1
The text was updated successfully, but these errors were encountered:
While running the application i get the below error in the application. Please guide me to solve it.
RuntimeError: stack expects each tensor to be equal size, but got [1, 64, 15, 9] at entry 0 and [1, 64, 16, 10] at entry 1
The exact error happening in the below line
prediction = model_type.end2end_detect(image, valid_tfms, model, class_map=class_map, detection_threshold=0.5)
Complete traceback code
The text was updated successfully, but these errors were encountered: