Spaces:
Runtime error
Runtime error
Create base.py
Browse files
3rdparty/densepose/converters/base.py
ADDED
|
@@ -0,0 +1,90 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Copyright (c) Facebook, Inc. and its affiliates.
|
| 2 |
+
|
| 3 |
+
from typing import Any, Tuple, Type
|
| 4 |
+
import torch
|
| 5 |
+
|
| 6 |
+
|
| 7 |
+
class BaseConverter:
|
| 8 |
+
"""
|
| 9 |
+
Converter base class to be reused by various converters.
|
| 10 |
+
Converter allows one to convert data from various source types to a particular
|
| 11 |
+
destination type. Each source type needs to register its converter. The
|
| 12 |
+
registration for each source type is valid for all descendants of that type.
|
| 13 |
+
"""
|
| 14 |
+
|
| 15 |
+
@classmethod
|
| 16 |
+
def register(cls, from_type: Type, converter: Any = None):
|
| 17 |
+
"""
|
| 18 |
+
Registers a converter for the specified type.
|
| 19 |
+
Can be used as a decorator (if converter is None), or called as a method.
|
| 20 |
+
Args:
|
| 21 |
+
from_type (type): type to register the converter for;
|
| 22 |
+
all instances of this type will use the same converter
|
| 23 |
+
converter (callable): converter to be registered for the given
|
| 24 |
+
type; if None, this method is assumed to be a decorator for the converter
|
| 25 |
+
"""
|
| 26 |
+
|
| 27 |
+
if converter is not None:
|
| 28 |
+
cls._do_register(from_type, converter)
|
| 29 |
+
|
| 30 |
+
def wrapper(converter: Any) -> Any:
|
| 31 |
+
cls._do_register(from_type, converter)
|
| 32 |
+
return converter
|
| 33 |
+
|
| 34 |
+
return wrapper
|
| 35 |
+
|
| 36 |
+
@classmethod
|
| 37 |
+
def _do_register(cls, from_type: Type, converter: Any):
|
| 38 |
+
cls.registry[from_type] = converter # pyre-ignore[16]
|
| 39 |
+
|
| 40 |
+
@classmethod
|
| 41 |
+
def _lookup_converter(cls, from_type: Type) -> Any:
|
| 42 |
+
"""
|
| 43 |
+
Perform recursive lookup for the given type
|
| 44 |
+
to find registered converter. If a converter was found for some base
|
| 45 |
+
class, it gets registered for this class to save on further lookups.
|
| 46 |
+
Args:
|
| 47 |
+
from_type: type for which to find a converter
|
| 48 |
+
Return:
|
| 49 |
+
callable or None - registered converter or None
|
| 50 |
+
if no suitable entry was found in the registry
|
| 51 |
+
"""
|
| 52 |
+
if from_type in cls.registry: # pyre-ignore[16]
|
| 53 |
+
return cls.registry[from_type]
|
| 54 |
+
for base in from_type.__bases__:
|
| 55 |
+
converter = cls._lookup_converter(base)
|
| 56 |
+
if converter is not None:
|
| 57 |
+
cls._do_register(from_type, converter)
|
| 58 |
+
return converter
|
| 59 |
+
return None
|
| 60 |
+
|
| 61 |
+
@classmethod
|
| 62 |
+
def convert(cls, instance: Any, *args, **kwargs):
|
| 63 |
+
"""
|
| 64 |
+
Convert an instance to the destination type using some registered
|
| 65 |
+
converter. Does recursive lookup for base classes, so there's no need
|
| 66 |
+
for explicit registration for derived classes.
|
| 67 |
+
Args:
|
| 68 |
+
instance: source instance to convert to the destination type
|
| 69 |
+
Return:
|
| 70 |
+
An instance of the destination type obtained from the source instance
|
| 71 |
+
Raises KeyError, if no suitable converter found
|
| 72 |
+
"""
|
| 73 |
+
instance_type = type(instance)
|
| 74 |
+
converter = cls._lookup_converter(instance_type)
|
| 75 |
+
if converter is None:
|
| 76 |
+
if cls.dst_type is None: # pyre-ignore[16]
|
| 77 |
+
output_type_str = "itself"
|
| 78 |
+
else:
|
| 79 |
+
output_type_str = cls.dst_type
|
| 80 |
+
raise KeyError(f"Could not find converter from {instance_type} to {output_type_str}")
|
| 81 |
+
return converter(instance, *args, **kwargs)
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
IntTupleBox = Tuple[int, int, int, int]
|
| 85 |
+
|
| 86 |
+
|
| 87 |
+
def make_int_box(box: torch.Tensor) -> IntTupleBox:
|
| 88 |
+
int_box = [0, 0, 0, 0]
|
| 89 |
+
int_box[0], int_box[1], int_box[2], int_box[3] = tuple(box.long().tolist())
|
| 90 |
+
return int_box[0], int_box[1], int_box[2], int_box[3]
|