First of all, thanks for the amazing research. I am super interested in this design generation research.

I would like to get cleaner-looking results to see. In your paper, I found you got a pair-wise comparison with raw segmentation and also vector floorplan.

I would like to check the results from vector floorplan visualization.

If it is in your github repo already, could you tell me where it is? I didn't see a description of it.

And I have a question about the floorplan result. Once I got the testing result from test.py with "data/json" using pre-trained weights, I found that some of the results are missing the entrance door. (filename: 7513.json, 18477.json, 19307.json, 36233.json, 45012.json, 45161,json)

Do you know the reason? I suspect entrance doors are overlapped by other masks.

Traceback (most recent call last): File "test.py", line 11, in from dataset.floorplan_dataset_maps_functional_high_res import FloorplanGraphDataset, floorplan_collate_fn File "/data/houseganpp/dataset/floorplan_dataset_maps_functional_high_res.py", line 28, in from misc.utils import ROOM_CLASS, ID_COLOR File "/data/houseganpp/misc/utils.py", line 30, in from pygraphviz import * ModuleNotFoundError: No module named 'pygraphviz'

Hi, I noticed that the code using input vector is 18-d ,instead of 12-d vector in the paper. So, I am so curious why you did that, and what benefit that can make. thanks for any reply

Hi,

I am trying to reproduce the results of your paper and I am getting an error while loading data. The error is the following:

113 ./data/rplan/45776.json [Epoch 0/200] [Batch 111/379] [D loss: 9.999077] [G loss: 81.515854] [L1 loss: 83.728096] Traceback (most recent call last): File "train.py", line 114, in for i, batch in enumerate(fp_loader): File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 530, in next data = self._next_data() File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1224, in _next_data 114 ./data/rplan/16164.json return self._process_data(data) File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1250, in _process_data data.reraise() File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/_utils.py", line 457, in reraise raise exception IndexError: Caught IndexError in DataLoader worker process 0. Original Traceback (most recent call last): File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/user/miniconda3/envs/houseganpp/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 49, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/user/houseganpp/dataset/floorplan_dataset_maps_functional_high_res.py", line 135, in getitem graph_nodes, graph_edges, rooms_mks = self.build_graph(rms_type, fp_eds, eds_to_rms) File "/home/user/houseganpp/dataset/floorplan_dataset_maps_functional_high_res.py", line 294, in build_graph poly = self.make_sequence(np.array([fp_eds[l][:4] for l in eds_poly]))[0] File "/home/user/houseganpp/dataset/floorplan_dataset_maps_functional_high_res.py", line 189, in make_sequence v_curr = tuple(edges[0][:2]) IndexError: index 0 is out of bounds for axis 0 with size 0

I have built the database with the repository https://github.com/sepidsh/Housegan-data-reader

I attach the file with the error, but I think that the error is not in the file but in the dataloader. When I feed just this file to the model, it works. 16164.zip

Have you had this error before? Do you know how to solve it?

I use the code in misc/read_floorplan.py to process the RPLAN dataset,

but I find the bboxes is not computed，and always [] !!!!!

So, how to get the bboxes

bboxes, edges, ed_rm = [], [], []
info=dict() for w_i in range(len(walls)): edges.append([((walls[w_i][0]-min_x)/lenx),((walls[w_i][1]-min_y)/leny),((walls[w_i][2]-min_x)/lenx),((walls[w_i][3]-min_y)/leny),walls[w_i][5],walls[w_i][8]]) if(walls[w_i][6]==-1): ed_rm.append([walls[w_i][7]]) elif(walls[w_i][7]==-1): ed_rm.append([walls[w_i][6]]) else: ed_rm.append([walls[w_i][6],walls[w_i][7]])

for i in range(len(poly)):
    p=poly[i]
    pm=[]
    for p_i in range((p)):
            if(p_i%2==0):
                pm.append(([edges[km+p_i][0],edges[km+p_i][1]]))
            else:
                pm.append(([edges[km+p_i][2],edges[km+p_i][3]]))
    km=km+p
info['room_type'] = room_type
info['boxes'] = bboxes
info['edges'] = edges
info['ed_rm'] = ed_rm

Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount("/content/drive", force_remount=True). usage: ipykernel_launcher.py [-h] [--n_cpu N_CPU] [--batch_size BATCH_SIZE] [--checkpoint CHECKPOINT] [--data_path DATA_PATH] [--out OUT] ipykernel_launcher.py: error: unrecognized arguments: -f /root/.local/share/jupyter/runtime/kernel-2b829f88-b0ca-4d50-b119-ca22aa9df5a4.json An exception has occurred, use %tb to see the full traceback.

SystemExit: 2