(self, text, size, qr_version, error_correction, box_size, border)
| 1155 | CATEGORY = "Masquerade Nodes" |
| 1156 | |
| 1157 | def create_qr_code(self, text, size, qr_version, error_correction, box_size, border): |
| 1158 | ensure_package("qrcode") |
| 1159 | import qrcode |
| 1160 | if error_correction =="L": |
| 1161 | error_level = qrcode.constants.ERROR_CORRECT_L |
| 1162 | elif error_correction =="M": |
| 1163 | error_level = qrcode.constants.ERROR_CORRECT_M |
| 1164 | elif error_correction =="Q": |
| 1165 | error_level = qrcode.constants.ERROR_CORRECT_Q |
| 1166 | else: |
| 1167 | error_level = qrcode.constants.ERROR_CORRECT_H |
| 1168 | |
| 1169 | qr = qrcode.QRCode( |
| 1170 | version=qr_version, |
| 1171 | error_correction=error_level, |
| 1172 | box_size=box_size, |
| 1173 | border=border) |
| 1174 | qr.add_data(text) |
| 1175 | qr.make(fit=True) |
| 1176 | img = qr.make_image(fill_color="black", back_color="white") |
| 1177 | img = img.resize((size,size)) |
| 1178 | # Convert img (a PIL Image) into a torch tensor |
| 1179 | tensor = torch.from_numpy(np.array(img)) |
| 1180 | return (tensor2rgb(tensor.unsqueeze(0)),) |
| 1181 | |
| 1182 | def rgb2hsv(rgb): |
| 1183 | # rgb is a tensor in the form [B, H, W, C] |
nothing calls this directly
no test coverage detected