image image | mask image | instance_masks images list | boxes list | n_instances int32 | roi_id int32 | split string |
|---|---|---|---|---|---|---|
[
[
226,
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278,
248
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[
108,
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159,
232
],
[
170,
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222,
232
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[
276,
157,
330,
203
],
[
129,
103,
181,
150
],
[
211,
257,
262,
301
]
] | 6 | 0 | train | |||
[
[
227,
269,
255,
304
]
] | 1 | 1 | train | |||
[
[
187,
94,
251,
132
],
[
100,
200,
153,
242
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[
200,
213,
234,
241
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[
263,
217,
298,
244
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[
193,
258,
247,
289
],
[
135,
129,
192,
177
],
[
105,
243,
155,
282
],
[
122... | 10 | 2 | train | |||
[
[
179,
72,
235,
127
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[
203,
138,
260,
193
],
[
119,
73,
176,
129
],
[
53,
179,
111,
235
]
] | 4 | 3 | train | |||
[
[
87,
168,
119,
195
],
[
139,
240,
171,
267
],
[
157,
149,
223,
177
],
[
57,
207,
113,
247
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[
164,
213,
196,
240
],
[
242,
260,
299,
300
],
[
217,
126,
274,
168
],
[
211,... | 9 | 4 | train | |||
[
[
141,
125,
171,
157
],
[
93,
153,
140,
207
],
[
114,
205,
161,
257
],
[
231,
187,
276,
238
],
[
206,
255,
241,
307
],
[
288,
167,
331,
218
],
[
191,
123,
237,
175
]
] | 7 | 5 | train | |||
[
[
126,
184,
170,
242
],
[
159,
296,
204,
355
],
[
256,
104,
298,
159
]
] | 3 | 6 | train | |||
[
[
233,
140,
288,
200
],
[
149,
64,
206,
122
],
[
226,
93,
258,
128
],
[
144,
150,
203,
212
]
] | 4 | 7 | train | |||
[
[
154,
292,
190,
323
],
[
108,
131,
168,
188
],
[
119,
230,
180,
286
],
[
260,
207,
294,
239
],
[
131,
163,
192,
221
],
[
180,
225,
239,
279
]
] | 6 | 8 | train | |||
[
[
98,
110,
139,
166
],
[
256,
66,
274,
121
],
[
221,
78,
241,
135
],
[
151,
88,
188,
142
]
] | 4 | 9 | train | |||
[
[
260,
92,
293,
120
],
[
146,
147,
204,
191
],
[
132,
206,
191,
250
],
[
289,
238,
348,
282
],
[
161,
266,
220,
311
],
[
112,
122,
170,
166
]
] | 6 | 10 | train | |||
[
[
75,
169,
116,
221
],
[
111,
224,
160,
276
],
[
209,
285,
240,
316
],
[
106,
138,
147,
191
]
] | 4 | 11 | train | |||
[
[
176,
179,
218,
227
],
[
101,
231,
147,
281
],
[
148,
92,
178,
152
],
[
232,
207,
259,
233
],
[
282,
185,
307,
238
]
] | 5 | 12 | train | |||
[
[
159,
143,
213,
192
],
[
158,
268,
207,
310
],
[
255,
264,
307,
295
],
[
109,
310,
164,
340
],
[
177,
208,
234,
242
]
] | 5 | 13 | train | |||
[
[
292,
166,
341,
212
],
[
191,
282,
224,
307
],
[
232,
196,
265,
225
]
] | 3 | 14 | train | |||
[
[
90,
177,
154,
232
],
[
166,
193,
230,
248
],
[
148,
131,
210,
186
],
[
251,
71,
314,
126
],
[
147,
305,
183,
339
]
] | 5 | 15 | train | |||
[
[
205,
153,
260,
209
]
] | 1 | 16 | train | |||
[
[
178,
262,
223,
317
],
[
102,
185,
144,
239
]
] | 2 | 17 | train | |||
[
[
224,
276,
262,
312
],
[
142,
211,
192,
268
],
[
235,
177,
272,
211
],
[
190,
111,
246,
165
],
[
103,
124,
156,
177
],
[
158,
68,
212,
121
],
[
295,
132,
357,
190
]
] | 7 | 18 | train | |||
[
[
60,
125,
113,
167
],
[
175,
196,
230,
239
],
[
88,
154,
142,
198
],
[
234,
132,
290,
175
],
[
147,
149,
201,
192
],
[
192,
227,
247,
271
],
[
129,
256,
184,
300
],
[
251,... | 9 | 19 | train | |||
[
[
270,
131,
324,
169
],
[
218,
138,
247,
169
],
[
101,
151,
134,
184
],
[
157,
191,
189,
224
],
[
219,
282,
281,
328
],
[
114,
46,
144,
73
],
[
157,
260,
216,
320
],
[
133,... | 9 | 20 | train | |||
[
[
253,
200,
311,
229
],
[
115,
271,
172,
299
],
[
173,
145,
235,
177
]
] | 3 | 21 | train | |||
[
[
80,
218,
109,
247
],
[
238,
258,
272,
289
],
[
103,
125,
150,
156
],
[
44,
199,
74,
226
],
[
209,
176,
263,
213
],
[
109,
168,
159,
205
],
[
204,
104,
259,
121
],
[
199,
... | 9 | 22 | train | |||
[
[
148,
197,
196,
259
],
[
234,
86,
273,
155
],
[
136,
259,
185,
321
],
[
106,
120,
154,
180
],
[
141,
127,
179,
195
],
[
209,
253,
259,
316
],
[
300,
116,
340,
187
],
[
118... | 10 | 23 | train | |||
[
[
289,
209,
347,
264
],
[
117,
173,
165,
223
]
] | 2 | 24 | train | |||
[
[
139,
154,
201,
201
],
[
73,
157,
130,
201
],
[
218,
118,
291,
171
],
[
222,
213,
287,
256
],
[
129,
255,
183,
292
],
[
81,
247,
131,
283
],
[
111,
64,
178,
120
],
[
116,
... | 10 | 25 | train | |||
[
[
150,
265,
177,
297
],
[
186,
86,
220,
130
],
[
127,
143,
176,
198
],
[
179,
167,
231,
229
]
] | 4 | 26 | train | |||
[
[
108,
141,
138,
195
],
[
252,
174,
269,
245
],
[
206,
155,
239,
212
],
[
265,
288,
301,
345
],
[
203,
81,
236,
139
],
[
173,
224,
206,
279
],
[
99,
285,
129,
337
]
] | 7 | 27 | train | |||
[
[
216,
197,
267,
243
],
[
260,
172,
287,
201
]
] | 2 | 28 | train | |||
[
[
320,
247,
347,
268
],
[
231,
117,
301,
142
],
[
261,
208,
314,
242
],
[
202,
216,
234,
239
],
[
72,
143,
141,
184
],
[
132,
232,
189,
264
],
[
227,
264,
278,
293
],
[
252... | 8 | 29 | train | |||
[
[
122,
257,
155,
288
],
[
277,
150,
337,
201
],
[
182,
114,
241,
164
],
[
61,
184,
118,
233
],
[
129,
155,
189,
196
],
[
243,
225,
302,
274
],
[
173,
229,
231,
278
]
] | 7 | 30 | train | |||
[
[
70,
125,
123,
167
]
] | 1 | 31 | train | |||
[
[
188,
100,
238,
152
]
] | 1 | 32 | train | |||
[
[
113,
252,
150,
300
],
[
163,
103,
200,
152
],
[
246,
86,
285,
135
],
[
158,
247,
182,
275
],
[
237,
152,
275,
202
],
[
178,
182,
203,
209
],
[
262,
223,
285,
281
]
] | 7 | 33 | train | |||
[
[
124,
133,
172,
190
],
[
277,
194,
315,
235
],
[
163,
247,
218,
315
],
[
216,
175,
273,
241
],
[
235,
54,
289,
111
],
[
190,
127,
241,
184
],
[
138,
79,
185,
132
]
] | 7 | 34 | train | |||
[
[
186,
231,
242,
280
],
[
237,
127,
270,
159
]
] | 2 | 35 | train | |||
[
[
121,
127,
176,
168
],
[
253,
179,
310,
215
],
[
86,
271,
131,
300
],
[
197,
115,
257,
157
]
] | 4 | 36 | train | |||
[
[
89,
133,
145,
188
],
[
140,
279,
189,
328
],
[
36,
143,
88,
195
],
[
167,
80,
204,
115
],
[
159,
149,
212,
202
]
] | 5 | 37 | train | |||
[
[
100,
164,
148,
216
],
[
156,
120,
204,
171
],
[
240,
105,
279,
156
],
[
259,
233,
288,
263
],
[
157,
241,
195,
293
],
[
219,
246,
267,
297
]
] | 6 | 38 | train | |||
[
[
130,
179,
179,
237
],
[
208,
252,
258,
312
],
[
205,
129,
252,
184
],
[
83,
165,
127,
218
],
[
156,
135,
206,
191
],
[
172,
261,
204,
299
],
[
143,
99,
172,
132
],
[
250,... | 8 | 39 | train | |||
[
[
95,
215,
132,
275
],
[
109,
50,
146,
111
],
[
160,
137,
196,
197
]
] | 3 | 40 | train | |||
[
[
145,
223,
175,
252
],
[
114,
118,
162,
170
],
[
233,
172,
284,
225
],
[
154,
255,
201,
304
],
[
223,
130,
255,
161
],
[
87,
174,
124,
226
],
[
178,
83,
209,
114
],
[
136,... | 8 | 41 | train | |||
[
[
128,
105,
160,
149
],
[
92,
166,
122,
209
]
] | 2 | 42 | train | |||
[
[
178,
107,
223,
140
],
[
269,
217,
295,
242
],
[
271,
134,
316,
169
],
[
107,
142,
151,
176
],
[
142,
182,
188,
217
],
[
198,
191,
245,
227
],
[
100,
262,
147,
299
],
[
10... | 9 | 43 | train | |||
[
[
75,
162,
138,
211
],
[
242,
246,
306,
295
],
[
200,
231,
237,
263
],
[
184,
138,
249,
187
],
[
279,
187,
351,
226
],
[
108,
112,
145,
143
],
[
183,
277,
220,
308
]
] | 7 | 44 | train | |||
[
[
230,
129,
263,
154
],
[
119,
258,
194,
303
],
[
320,
209,
353,
238
],
[
210,
201,
274,
249
],
[
165,
112,
225,
153
],
[
103,
137,
168,
174
],
[
102,
173,
170,
213
]
] | 7 | 45 | train | |||
[
[
117,
123,
180,
144
],
[
71,
237,
140,
262
],
[
212,
179,
245,
205
],
[
87,
203,
119,
229
],
[
152,
216,
211,
256
],
[
260,
129,
293,
153
],
[
54,
130,
107,
165
]
] | 7 | 46 | train | |||
[
[
186,
138,
232,
193
],
[
258,
137,
297,
196
],
[
118,
233,
163,
290
],
[
232,
220,
282,
281
],
[
147,
105,
191,
159
],
[
128,
67,
162,
121
],
[
133,
181,
178,
236
],
[
163... | 8 | 47 | train | |||
[
[
270,
184,
296,
252
],
[
188,
182,
230,
241
],
[
118,
249,
147,
322
],
[
226,
130,
254,
199
],
[
265,
139,
291,
170
],
[
175,
104,
217,
161
],
[
151,
256,
194,
317
],
[
96... | 8 | 48 | train | |||
[
[
219,
204,
278,
266
],
[
290,
197,
350,
259
],
[
171,
247,
229,
308
],
[
199,
124,
258,
186
]
] | 4 | 49 | train | |||
[
[
249,
187,
298,
241
],
[
205,
133,
256,
190
],
[
94,
130,
151,
191
],
[
141,
103,
177,
138
],
[
125,
239,
168,
301
],
[
155,
26,
211,
89
]
] | 6 | 50 | train | |||
[
[
84,
157,
119,
189
]
] | 1 | 51 | train | |||
[
[
160,
83,
191,
118
],
[
122,
252,
161,
301
],
[
217,
109,
268,
167
],
[
191,
250,
238,
302
],
[
183,
116,
226,
170
]
] | 5 | 52 | train | |||
[
[
209,
94,
266,
152
],
[
211,
212,
265,
267
],
[
265,
164,
317,
218
]
] | 3 | 53 | train | |||
[
[
227,
241,
281,
286
],
[
192,
151,
246,
197
],
[
117,
123,
170,
169
],
[
120,
182,
151,
211
],
[
196,
197,
227,
226
],
[
264,
173,
321,
208
],
[
142,
85,
196,
131
],
[
160... | 10 | 54 | train | |||
[
[
202,
251,
255,
306
],
[
221,
135,
271,
186
],
[
249,
201,
298,
253
],
[
77,
154,
133,
209
]
] | 4 | 55 | train | |||
[
[
298,
171,
362,
218
],
[
137,
141,
174,
172
],
[
43,
148,
108,
196
]
] | 3 | 56 | train | |||
[
[
149,
81,
180,
113
],
[
220,
84,
265,
135
],
[
161,
210,
213,
264
],
[
155,
171,
187,
204
],
[
118,
228,
170,
282
],
[
265,
181,
317,
235
]
] | 6 | 57 | train | |||
[
[
153,
64,
200,
126
],
[
173,
223,
213,
294
],
[
120,
58,
159,
125
],
[
263,
170,
315,
237
],
[
116,
268,
146,
307
],
[
151,
157,
200,
222
],
[
221,
90,
272,
155
],
[
284,
... | 9 | 58 | train | |||
[
[
97,
164,
154,
217
],
[
259,
209,
313,
250
],
[
171,
73,
227,
128
],
[
186,
213,
218,
244
],
[
161,
301,
214,
341
],
[
104,
232,
160,
283
],
[
212,
162,
265,
214
]
] | 7 | 59 | train | |||
[
[
156,
272,
215,
324
],
[
224,
329,
258,
365
],
[
209,
239,
266,
290
],
[
166,
98,
222,
152
],
[
272,
182,
326,
237
],
[
92,
226,
151,
279
],
[
83,
179,
141,
230
],
[
179,
... | 8 | 60 | train | |||
[
[
266,
162,
320,
202
],
[
94,
254,
125,
279
],
[
178,
103,
210,
132
],
[
247,
239,
299,
276
]
] | 4 | 61 | train | |||
[
[
300,
284,
346,
309
],
[
289,
131,
344,
167
],
[
222,
230,
273,
259
],
[
163,
126,
196,
153
],
[
75,
173,
135,
206
],
[
59,
114,
123,
151
],
[
93,
215,
149,
245
],
[
155,
... | 10 | 62 | train | |||
[
[
205,
135,
250,
197
],
[
152,
284,
196,
347
],
[
116,
93,
160,
155
]
] | 3 | 63 | train | |||
[
[
102,
107,
134,
152
],
[
200,
115,
224,
140
],
[
196,
197,
230,
243
],
[
115,
262,
146,
305
]
] | 4 | 64 | train | |||
[
[
123,
119,
169,
172
]
] | 1 | 65 | train | |||
[
[
244,
194,
294,
251
],
[
123,
261,
174,
317
],
[
224,
247,
274,
303
],
[
178,
256,
228,
313
],
[
152,
85,
202,
140
]
] | 5 | 66 | train | |||
[
[
230,
163,
277,
215
],
[
152,
325,
181,
355
],
[
139,
143,
194,
207
],
[
205,
273,
250,
323
],
[
68,
155,
125,
216
]
] | 5 | 67 | train | |||
[
[
229,
134,
267,
188
],
[
189,
212,
229,
269
],
[
250,
214,
289,
269
],
[
198,
175,
229,
206
]
] | 4 | 68 | train | |||
[
[
259,
201,
287,
231
],
[
267,
111,
309,
166
],
[
189,
104,
214,
133
],
[
183,
288,
221,
340
],
[
101,
217,
133,
263
],
[
144,
139,
164,
198
],
[
107,
128,
139,
175
],
[
19... | 9 | 69 | train | |||
[
[
126,
220,
168,
278
],
[
234,
162,
285,
219
],
[
101,
122,
152,
178
],
[
168,
255,
210,
313
],
[
172,
88,
222,
144
],
[
288,
144,
331,
202
],
[
77,
201,
119,
258
],
[
221,... | 9 | 70 | train | |||
[
[
210,
162,
254,
210
],
[
168,
178,
211,
225
],
[
251,
148,
297,
199
]
] | 3 | 71 | train | |||
[
[
148,
33,
209,
98
],
[
270,
181,
319,
234
]
] | 2 | 72 | train | |||
[
[
236,
138,
290,
191
],
[
144,
156,
203,
213
],
[
294,
193,
345,
247
],
[
276,
234,
329,
291
],
[
197,
276,
233,
312
],
[
199,
82,
247,
138
]
] | 6 | 73 | train | |||
[
[
174,
190,
228,
232
],
[
219,
281,
250,
306
],
[
226,
255,
257,
281
],
[
121,
217,
178,
245
],
[
78,
230,
129,
269
]
] | 5 | 74 | train | |||
[
[
248,
88,
301,
148
]
] | 1 | 75 | train | |||
[
[
53,
181,
102,
241
]
] | 1 | 76 | train | |||
[
[
230,
223,
285,
276
],
[
165,
140,
221,
193
],
[
164,
229,
219,
282
]
] | 3 | 77 | train | |||
[
[
262,
116,
294,
158
],
[
206,
102,
237,
144
],
[
132,
106,
164,
147
],
[
121,
286,
143,
309
],
[
177,
231,
199,
254
]
] | 5 | 78 | train | |||
[
[
211,
165,
246,
225
],
[
135,
238,
180,
289
],
[
124,
296,
152,
324
],
[
238,
162,
286,
217
],
[
108,
135,
151,
187
],
[
163,
88,
209,
142
],
[
169,
225,
198,
255
],
[
233... | 10 | 79 | train | |||
[
[
252,
143,
307,
187
]
] | 1 | 80 | train | |||
[
[
116,
121,
141,
196
],
[
211,
170,
244,
227
],
[
266,
179,
295,
232
],
[
184,
279,
219,
333
],
[
98,
218,
142,
282
],
[
261,
245,
291,
295
],
[
104,
284,
147,
344
],
[
189... | 9 | 81 | train | |||
[
[
207,
100,
243,
147
],
[
255,
285,
278,
310
],
[
100,
192,
145,
243
],
[
260,
198,
291,
241
],
[
210,
235,
246,
281
],
[
89,
106,
115,
171
],
[
138,
115,
162,
177
]
] | 7 | 82 | train | |||
[
[
274,
178,
320,
231
],
[
139,
224,
173,
257
],
[
184,
249,
233,
303
],
[
149,
26,
203,
89
],
[
183,
124,
235,
183
],
[
120,
98,
176,
160
],
[
237,
110,
286,
167
],
[
101,
... | 8 | 83 | train | |||
[
[
114,
117,
169,
158
],
[
107,
159,
136,
185
]
] | 2 | 84 | train | |||
[
[
281,
226,
350,
250
],
[
194,
221,
253,
258
],
[
212,
126,
271,
165
]
] | 3 | 85 | train | |||
[
[
116,
281,
177,
333
],
[
273,
168,
309,
203
],
[
256,
196,
318,
249
],
[
147,
303,
208,
360
]
] | 4 | 86 | train | |||
[
[
111,
149,
167,
201
],
[
47,
185,
93,
230
],
[
97,
243,
143,
287
],
[
265,
150,
328,
209
],
[
177,
200,
237,
250
],
[
155,
35,
196,
74
],
[
44,
153,
74,
181
]
] | 7 | 87 | train | |||
[
[
213,
180,
268,
233
],
[
187,
114,
219,
143
],
[
89,
233,
133,
285
],
[
182,
259,
216,
293
],
[
119,
159,
170,
209
],
[
145,
212,
197,
266
],
[
67,
178,
116,
228
],
[
254,... | 9 | 88 | train | |||
[
[
213,
79,
246,
134
],
[
118,
144,
147,
195
]
] | 2 | 89 | train | |||
[
[
241,
129,
283,
181
],
[
85,
221,
123,
272
],
[
147,
163,
187,
215
],
[
255,
234,
297,
289
],
[
212,
95,
253,
147
],
[
212,
227,
253,
280
]
] | 6 | 90 | train | |||
[
[
199,
231,
262,
274
],
[
50,
180,
83,
208
],
[
259,
130,
334,
182
],
[
143,
196,
208,
232
],
[
127,
133,
165,
164
],
[
284,
216,
325,
246
]
] | 6 | 91 | train | |||
[
[
118,
209,
148,
245
],
[
264,
146,
298,
220
],
[
197,
322,
227,
358
]
] | 3 | 92 | train | |||
[
[
155,
95,
212,
145
]
] | 1 | 93 | train | |||
[
[
176,
207,
235,
252
],
[
103,
160,
170,
194
],
[
143,
246,
208,
278
],
[
235,
130,
306,
165
],
[
209,
167,
278,
202
]
] | 5 | 94 | train | |||
[
[
238,
283,
272,
316
]
] | 1 | 95 | train | |||
[
[
255,
109,
279,
142
],
[
221,
188,
255,
248
],
[
221,
323,
244,
357
],
[
170,
258,
204,
319
],
[
117,
173,
150,
233
],
[
119,
82,
136,
155
],
[
192,
53,
226,
112
],
[
146,... | 8 | 96 | train | |||
[
[
113,
161,
174,
223
],
[
191,
131,
249,
191
],
[
175,
198,
235,
261
],
[
131,
69,
191,
130
],
[
117,
240,
177,
301
],
[
256,
158,
315,
219
],
[
255,
117,
312,
176
],
[
206... | 8 | 97 | train | |||
[
[
236,
199,
273,
231
]
] | 1 | 98 | train | |||
[
[
256,
257,
291,
317
]
] | 1 | 99 | train |
End of preview. Expand in Data Studio
SBD QR Subset — low resolution
A mirror of the low-resolution ROI split of the Synthetic Barcode Dataset (Quenum, Wang, Zakhor), repackaged from 749,682 loose files into parquet.
| split | ROIs | instances |
|---|---|---|
| train | 80,000 | 439,731 |
| validation | 10,000 | 55,072 |
| test | 10,000 | 54,876 |
| total | 100,000 | 549,679 |
Why this repackaging exists
Upstream, this split is three-quarters of a million individual PNG and JPEG files. That is unpleasant to move, impossible to browse, and slow to load. Here each ROI is one row carrying its image, its combined mask, all of its per-instance masks, and its bounding boxes — so the whole thing loads with one call and renders in the dataset viewer.
Fields
| field | notes |
|---|---|
image |
the 400×400 grayscale ROI |
mask |
the combined mask for the ROI |
instance_masks |
list of per-instance masks, one per barcode |
boxes |
list of [x1, y1, x2, y2], aligned index-for-index with instance_masks |
n_instances |
number of barcodes in the ROI |
roi_id |
upstream ROI index (roi<N>.png ↔ img_<N> in all_bboxes.json) |
The box↔mask alignment was verified, not assumed
boxes[k] and instance_masks[k] are the same object. The packer checked the
count of boxes against the count of instance-mask files for every one of the
100,000 ROIs and found zero mismatches, and no ROI was missing its combined
mask. If they had disagreed, the join would have been silently wrong in a way no
loader would flag — so it is checked rather than trusted.
Usage
from datasets import load_dataset
ds = load_dataset("devmandan/sbd-qr-subset", split="train", streaming=True)
row = next(iter(ds))
row["image"], row["mask"], row["instance_masks"][0], row["boxes"][0]
# crowded ROIs
full = load_dataset("devmandan/sbd-qr-subset", split="test")
crowded = full.filter(lambda r: r["n_instances"] >= 8)
streaming=True is worth using here — the train split is ~3 GB.
Scope, stated plainly
This mirror carries the low_resolution ROI split only. The upstream SBD
release also has ultra-high-resolution splits and full-scene imagery that are
not included here. Do not describe results on this mirror as results on SBD.
It is also a barcode dataset covering multiple symbologies, not a QR-only one; it appears in a QR collection for its scale and its instance masks.
Citation
@misc{sbd_synthetic_barcode_dataset,
title = {Synthetic Barcode Dataset (SBD)},
author = {Quenum, Jerome and Wang, Kehan and Zakhor, Avideh},
note = {Synthetic barcode detection and segmentation dataset}
}
Licence: CC BY 4.0 as recorded in the dataset registry (the authors' code repository is separately MIT). Attribute the authors above, not this mirror.
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