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Repulsion Loss
dic = {0: [], 1: [], 2: [], 3: [], 4: [], 5: [], 6: [], 7: [], 8: [], 9: [], 10: [], 11: [], 12: [], 13: [], 14: [], 15: [], 16: [], 17: [], 18: [], 19: [], 20: [], 21: [], 22: [], 23: [], 24: [], 25: [], 26: [], 27: [], 28: [], 29: [], 30: [], 31: [], 32: [], 33: [], 34: [], 35: [], 36: [], 37: [], 38: [], 39: [], 40: [], 41: [], 42: [], 43: [], 44: [], 45: [], 46: [], 47: [], 48: [], 49: [], 50: [], 51: [], 52: [], 53: [], 54: [], 55: [], 56: [], 57: [], 58: [], 59: [], 60: [], 61: [], 62: [], 63: [], 64: [], 65: [], 66: [], 67: [], 68: [], 69: [], 70: [], 71: [], 72: [], 73: [], 74: [], 75: [], 76: [], 77: [], 78: [], 79: [], 80: [], 81: [], 82: [], 83: [], 84: [], 85: [], 86: [], 87: [], 88: [], 89: [], 90: [], 91: [], 92: [], 93: [], 94: [], 95: [], 96: [], 97: [], 98: [], 99: [], 100: [], 101: [], 102: [], 103: [], 104: [], 105: [], 106: [], 107: [], 108: [], 109: [], 110: [], 111: [], 112: [], 113: [], 114: [], 115: [], 116: [], 117: [], 118: [], 119: [], 120: [], 121: [], 122: [], 123: [], 124: [], 125: [], 126: [], 127: [], 128: [], 129: [], 130: [], 131: [], 132: [], 133: [], 134: [], 135: [], 136: [], 137: [], 138: [], 139: [], 140: [], 141: [], 142: [], 143: [], 144: [], 145: [], 146: [], 147: [], 148: [], 149: []}
为什么这个dic设置成150,是根据什么设置的?
lrep = self.hyp['alpha'] * lrepGT / 3.0 + self.hyp['beta'] * lrepBox / 3.0
还有rep损失这个超参数是根据数据集自己调整的吗?除以3.0是为什么呢? 感谢!
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因为int(value)这个key是batch size,这个是根据你batch size设定的,如果你的batch size是16,那你只要设计的key包含0-16就可以了,其他的没有用。或者你也可以换个写法,就不用写这么多key了,比如dic.setdefault(int(value), []).append(indexs) 这个3.0就是一个超参数,以前debug时候写的,后来就没删。你也可以把这个3.0除在那个超参数文件里
好的谢谢,请问您有试过Repulsion Loss中默认的超参数0.5吗?效果怎么样
dic = {i: [] for i in range(150)}
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为什么这个dic设置成150,是根据什么设置的?
还有rep损失这个超参数是根据数据集自己调整的吗?除以3.0是为什么呢?
感谢!
The text was updated successfully, but these errors were encountered: