question ：dataset & Results

[JerkyT]

Hello,Thanks for your code, but i have some question:

The link from project has missing data : single-view PCD i have same question with https://github.com/SMohammadi89/PointView-GCN/issues/2 I run the PointView-GCN with PointNet++ on ModelNet40, the classification result is only 92.8%

[SMohammadi89]

Hi @JerkyT, could you please tell me what is the classification result you get from PointNet++ using our dataset

[JerkyT]

Thanks for your reply@SMohammadi89， I followed the tips and do：

cd Feature_extraction
python main.py

the pointnet++ model file is：pointnet2_cls.py and the ccheckpoint is pointnet_on_single_view.pth and the output result like this:

[1. 0.88988095 0.96775794 0.76201923 0.92509921 0.97271825 0.9525 0.99900794 0.97172619 0.91666667 0.7225 0.92 0.82349537 0.92548077 0.89351852 0.18 0.94451531 0.99950397 0.99759615 0.86057692 0.98317308 0.94146825 0.98214286 0.66724537 0.90885417 0.955 0.90396341 0.78 0.9265 0.81 0.939 0.9075 0.855 0.7755 0.9125 0.985 0.888 0.817 0.54 0.72395833] test Instance Accuracy: 0.904210, Class Accuracy: 0.870659

[JerkyT]

Hellow, the other question : i want to use your code. but~ I compared your dataset with the dataset from the ModelNet40 official website and found that these samples are missing

**Test** : [glass_box_0219, glass_box_0221, glass_box_0241, glass_box_0213, glass_box_0211, glass_box_0242, xbox_0123, glass_box_0229, piano_0232, plant_0276, glass_box_0208, glass_box_0260, glass_box_0249, glass_box_0185, glass_box_0245, glass_box_0256, glass_box_0232, glass_box_0253, person_0093, glass_box_0254, plant_0265, glass_box_0239, bowl_0078, glass_box_0255, glass_box_0193, glass_box_0216, glass_box_0248, cone_0179, glass_box_0215]
**Train** : [chair_0263, chair_0381, chair_0486, chair_0274, vase_0451, vase_0350, chair_0466, vase_0352, chair_0519, vase_0315, chair_0288, chair_0549, chair_0124, chair_0354, vase_0470, chair_0529, chair_0498, chair_0302, chair_0481, chair_0210, vase_0449, chair_0583, tent_0145, chair_0126, chair_0327, vase_0408, chair_0389, chair_0258, vase_0394, vase_0319, tent_0142, chair_0567, chair_0242, tent_0150, chair_0181, chair_0341, curtain_0054, person_0026, chair_0372, person_0058, chair_0226, vase_0457, chair_0262, tent_0144, chair_0767, vase_0423, chair_0577, chair_0589, vase_0337, plant_0078, chair_0415, chair_0290, vase_0365, chair_0272, chair_0127, chair_0277, chair_0248, vase_0371, vase_0471, chair_0798, chair_0584, chair_0499, chair_0405, vase_0344, chair_0536, vase_0441, door_0059, chair_0207, vase_0395, chair_0357, tent_0152, chair_0517, chair_0287, vase_0348, chair_0491, chair_0301, chair_0476, chair_0522, chair_0257, vase_0469, vase_0430, vase_0374, chair_0401, chair_0311, chair_0241, chair_0495, tent_0137, chair_0494, chair_0533, chair_0304, table_0361, vase_0364, chair_0581, vase_0434, chair_0504, chair_0452, chair_0370, chair_0550, chair_0587, chair_0265, chair_0358, chair_0280, vase_0393, chair_0292, chair_0228, chair_0547, chair_0794, chair_0376, chair_0410, tent_0139, chair_0220, chair_0490, vase_0391, chair_0791, chair_0371, bowl_0018, chair_0386, vase_0421, vase_0397, chair_0424, chair_0451, chair_0230, chair_0279, chair_0326, vase_0376, chair_0445, tent_0154, chair_0485, chair_0478, vase_0379, chair_0316, chair_0377, chair_0576, chair_0348, chair_0261, chair_0477, vase_0454, chair_0221, chair_0444, chair_0488, vase_0324, tent_0128, chair_0470, chair_0456, chair_0426, chair_0578, chair_0764, tent_0146, tent_0147, chair_0417, vase_0405, chair_0323, chair_0252, chair_0409, chair_0342, chair_0436, chair_0309, chair_0535, vase_0373, chair_0413, chair_0460, chair_0307, tent_0153, vase_0342, chair_0240, vase_0346, vase_0398, chair_0559, tent_0148, vase_0329, chair_0373, vase_0308, chair_0483, chair_0202, vase_0437, chair_0449, chair_0790, chair_0439, chair_0551, chair_0471, tent_0160, vase_0355, tent_0134, chair_0298, chair_0448, vase_0356, chair_0201, chair_0229, vase_0388, chair_0122, chair_0442, vase_0323, vase_0425, vase_0432, chair_0332, tent_0143, chair_0762, vase_0340, chair_0482, vase_0307, chair_0546, chair_0575, chair_0268, tent_0136, chair_0222, vase_0334, chair_0554, vase_0328, vase_0445, vase_0331, chair_0515, chair_0355, chair_0123, chair_0763, chair_0416, chair_0333, chair_0337, person_0015, vase_0385, chair_0227, chair_0570, vase_0453, vase_0409, chair_0434, chair_0188, cone_0008, chair_0421, chair_0541, vase_0357, vase_0313, vase_0305, chair_0792, chair_0289, vase_0380, chair_0187, chair_0349, vase_0462, vase_0360, chair_0503, tent_0159, vase_0389, chair_0530, chair_0374, vase_0375, tent_0119, chair_0294, chair_0509, chair_0524, chair_0266, chair_0766, vase_0383, chair_0256, tent_0161, chair_0340, vase_0400, chair_0545, chair_0236, vase_0407, chair_0233, chair_0548, chair_0244, vase_0417, chair_0350, chair_0331, vase_0403, chair_0351, chair_0245, chair_0474, chair_0308, chair_0518, vase_0381, vase_0456, chair_0453, vase_0306, vase_0411, person_0029, chair_0428, chair_0543, chair_0213, chair_0412, chair_0324, chair_0432, chair_0507, chair_0203, chair_0497, chair_0555, vase_0372, vase_0318, tent_0122, chair_0359, chair_0429, vase_0433, chair_0275, plant_0232, vase_0382, chair_0560, chair_0473, chair_0364, vase_0359, chair_0500, chair_0335, chair_0312, vase_0467, vase_0444, tent_0126, chair_0588, vase_0330, chair_0534, chair_0461, chair_0458, chair_0512, chair_0214, chair_0516, vase_0466, tent_0131, vase_0414, chair_0356, vase_0436, vase_0341, chair_0387, chair_0539, chair_0418, chair_0480, chair_0299, chair_0129, chair_0441, chair_0388, tent_0156, chair_0260, vase_0343, chair_0330, vase_0410, vase_0463, vase_0387, vase_0452, tent_0138, chair_0375, chair_0457, chair_0247, chair_0385, chair_0334, chair_0232, chair_0254, chair_0271, chair_0572, chair_0329, tv_stand_0114, tent_0162, vase_0442, chair_0310, chair_0586, vase_0338, vase_0464, vase_0325, chair_0492, tent_0125, chair_0208, chair_0246, vase_0473, chair_0561, tent_0120, tent_0133, chair_0425, vase_0327, vase_0448, chair_0769, chair_0328, chair_0259, chair_0297, vase_0415, vase_0420, vase_0321, chair_0215, vase_0422, chair_0472, chair_0128, chair_0438, chair_0206, tent_0124, chair_0205, vase_0458, chair_0564, chair_0520, chair_0338, chair_0423, tent_0121, chair_0795, vase_0419, chair_0513, chair_0435, chair_0562, chair_0566, chair_0283, stairs_0113, chair_0563, chair_0380, chair_0493, chair_0296, chair_0366, chair_0404, chair_0273, chair_0382, chair_0384, tent_0123, chair_0237, chair_0343, vase_0472, chair_0443, vase_0358, chair_0120, chair_0185, chair_0469, vase_0455, vase_0401, chair_0270, chair_0542, chair_0765, vase_0335, chair_0484, chair_0182, chair_0285, vase_0446, chair_0346, vase_0309, tent_0158, chair_0305, tent_0129, vase_0378, cone_0141, person_0051, chair_0556, chair_0573, vase_0349, chair_0574, chair_0315, chair_0420, chair_0235, chair_0383, chair_0318, chair_0223, chair_0532, vase_0326, vase_0351, chair_0544, person_0060, chair_0799, chair_0336, chair_0797, chair_0269, vase_0427, vase_0404, vase_0362, chair_0368, vase_0312, chair_0508, vase_0339, chair_0454, chair_0284, chair_0440, chair_0407, chair_0267, chair_0306, chair_0321, chair_0455, chair_0402, chair_0303, chair_0378, chair_0217, chair_0278, chair_0552, chair_0231, vase_0333, chair_0282, chair_0475, chair_0362, vase_0406, plant_0044, vase_0361, chair_0365, chair_0526, chair_0411, vase_0384, chair_0568, chair_0437, chair_0281, chair_0183, chair_0317, chair_0325, chair_0379, chair_0459, chair_0414, chair_0489, vase_0320, cone_0034, vase_0368, chair_0447, chair_0796, vase_0390, chair_0360, chair_0253, chair_0430, chair_0200, chair_0293, vase_0310, chair_0363, cone_0111, chair_0347, chair_0537, chair_0521, chair_0419, vase_0465, tent_0135, tent_0157, vase_0461, chair_0580, chair_0322, chair_0528, vase_0468, vase_0424, chair_0450, tent_0127, chair_0300, chair_0189, chair_0501, chair_0345, chair_0180, chair_0571, chair_0224, laptop_0140, chair_0234, chair_0502, vase_0475, vase_0474, chair_0204, vase_0316, tent_0130, vase_0428, chair_0339, vase_0322, chair_0406, vase_0347, chair_0585, chair_0184, chair_0467, vase_0311, tent_0132, chair_0255, vase_0412, tent_0163, vase_0426, vase_0377, vase_0396, chair_0446, vase_0336, person_0016, chair_0538, chair_0403, vase_0369, vase_0450, vase_0353, chair_0760, chair_0209, chair_0400, chair_0361, vase_0370, chair_0464, vase_0314, chair_0433, chair_0367, chair_0540, chair_0565, chair_0422, vase_0439, chair_0505, chair_0427, chair_0468, vase_0413, vase_0392, chair_0251, chair_0768, chair_0320, vase_0402, vase_0332, vase_0418, chair_0511, chair_0579, chair_0243, vase_0447, vase_0460, chair_0218, chair_0496, chair_0225, chair_0582, chair_0219, chair_0125, chair_0558, vase_0386, chair_0264, vase_0317, chair_0465, vase_0363, chair_0286, vase_0416, vase_0459, chair_0291, vase_0438, chair_0462, vase_0367, chair_0569, vase_0443, chair_0239, chair_0313, chair_0557, chair_0352, chair_0514, vase_0304, chair_0463, vase_0435, chair_0761, vase_0366, vase_0440, tent_0141, chair_0523, tent_0140, chair_0121, vase_0345, chair_0344, tent_0149, keyboard_0088, chair_0793, chair_0216, vase_0429, chair_0553, chair_0479, chair_0276, curtain_0124, chair_0211, person_0044, chair_0186, chair_0510, chair_0408, chair_0212, chair_0369, chair_0487, chair_0525, chair_0431, chair_0238, chair_0506, chair_0249, vase_0431, vase_0399, chair_0531, chair_0314, chair_0250, chair_0353, chair_0295, tent_0151, chair_0527, chair_0319]

i try to run ：

cd Dataset_rendering
python dataset_capturing.py --out-split-dir /train/ && python dataset_capturing.py --out-split-dir /test/

But it looks like I don't have the *'.ply'** file Could you please upload the full dataset？thank you very much！

[Qifengle12]

Hi, I was wondering what you did with the scanobjectnn dataset and the two different view configurations of 12 and 20 with the modelnet40 dataset?