Remove RGB -> BGR image conversion in Object Detection tutorial
_The documentation is not available anymore as the PR was closed or merged._ <details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.009443 / 0.011353 (-0.001910) | 0.005274 / 0.011008 (-0.005734) | 0.105950 / 0.038508 (0.067441) | 0.079947 / 0.023109 (0.056837) | 0.414248 / 0.275898 (0.138350) | 0.440611 / 0.323480 (0.117131) | 0.006779 / 0.007986 (-0.001206) | 0.004301 / 0.004328 (-0.000028) | 0.080616 / 0.004250 (0.076366) | 0.061425 / 0.037052 (0.024372) | 0.418460 / 0.258489 (0.159971) | 0.468108 / 0.293841 (0.174267) | 0.051090 / 0.128546 (-0.077456) | 0.014133 / 0.075646 (-0.061513) | 0.376121 / 0.419271 (-0.043151) | 0.070715 / 0.043533 (0.027182) | 0.415435 / 0.255139 (0.160296) | 0.457925 / 0.283200 (0.174725) | 0.053653 / 0.141683 (-0.088030) | 1.872681 / 1.452155 (0.420527) | 1.961187 / 1.492716 (0.468470) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.255829 / 0.018006 (0.237823) | 0.574224 / 0.000490 (0.573735) | 0.007597 / 0.000200 (0.007397) | 0.000098 / 0.000054 (0.000044) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.032562 / 0.037411 (-0.004849) | 0.097528 / 0.014526 (0.083003) | 0.113487 / 0.176557 (-0.063070) | 0.185670 / 0.737135 (-0.551465) | 0.118909 / 0.296338 (-0.177430) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.611441 / 0.215209 (0.396232) | 5.908576 / 2.077655 (3.830921) | 2.586758 / 1.504120 (1.082638) | 2.310199 / 1.541195 (0.769004) | 2.333396 / 1.468490 (0.864906) | 0.900884 / 4.584777 (-3.683893) | 5.438304 / 3.745712 (1.692591) | 4.806611 / 5.269862 (-0.463250) | 2.970631 / 4.565676 (-1.595046) | 0.097861 / 0.424275 (-0.326414) | 0.009873 / 0.007607 (0.002266) | 0.739553 / 0.226044 (0.513509) | 7.104953 / 2.268929 (4.836024) | 3.150128 / 55.444624 (-52.294497) | 2.469552 / 6.876477 (-4.406924) | 2.709206 / 2.142072 (0.567133) | 0.983081 / 4.805227 (-3.822147) | 0.205150 / 6.500664 (-6.295514) | 0.075947 / 0.075469 (0.000478) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.631255 / 1.841788 (-0.210532) | 24.213679 / 8.074308 (16.139370) | 21.514481 / 10.191392 (11.323089) | 0.220360 / 0.680424 (-0.460063) | 0.031663 / 0.534201 (-0.502538) | 0.516029 / 0.579283 (-0.063254) | 0.591461 / 0.434364 (0.157097) | 0.612398 / 0.540337 (0.072061) | 0.807609 / 1.386936 (-0.579328) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.009443 / 0.011353 (-0.001910) | 0.005510 / 0.011008 (-0.005498) | 0.085722 / 0.038508 (0.047214) | 0.076256 / 0.023109 (0.053146) | 0.604248 / 0.275898 (0.328349) | 0.596222 / 0.323480 (0.272742) | 0.006786 / 0.007986 (-0.001200) | 0.004135 / 0.004328 (-0.000193) | 0.085934 / 0.004250 (0.081683) | 0.065890 / 0.037052 (0.028838) | 0.592080 / 0.258489 (0.333591) | 0.624560 / 0.293841 (0.330719) | 0.048200 / 0.128546 (-0.080346) | 0.015477 / 0.075646 (-0.060169) | 0.097042 / 0.419271 (-0.322230) | 0.060513 / 0.043533 (0.016981) | 0.557171 / 0.255139 (0.302032) | 0.582057 / 0.283200 (0.298858) | 0.035678 / 0.141683 (-0.106005) | 1.894947 / 1.452155 (0.442792) | 1.956652 / 1.492716 (0.463936) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.268927 / 0.018006 (0.250921) | 0.566086 / 0.000490 (0.565597) | 0.007190 / 0.000200 (0.006990) | 0.000101 / 0.000054 (0.000047) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.042090 / 0.037411 (0.004679) | 0.109618 / 0.014526 (0.095092) | 0.126588 / 0.176557 (-0.049968) | 0.200426 / 0.737135 (-0.536709) | 0.127032 / 0.296338 (-0.169306) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.669773 / 0.215209 (0.454564) | 6.453417 / 2.077655 (4.375763) | 3.119147 / 1.504120 (1.615027) | 2.818632 / 1.541195 (1.277437) | 2.930880 / 1.468490 (1.462390) | 0.922164 / 4.584777 (-3.662612) | 5.769564 / 3.745712 (2.023852) | 4.885108 / 5.269862 (-0.384754) | 3.041640 / 4.565676 (-1.524037) | 0.100186 / 0.424275 (-0.324090) | 0.009417 / 0.007607 (0.001810) | 0.783138 / 0.226044 (0.557094) | 8.113361 / 2.268929 (5.844432) | 4.018630 / 55.444624 (-51.425995) | 3.246772 / 6.876477 (-3.629704) | 3.520690 / 2.142072 (1.378618) | 1.063686 / 4.805227 (-3.741541) | 0.218667 / 6.500664 (-6.281997) | 0.084169 / 0.075469 (0.008700) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.791949 / 1.841788 (-0.049839) | 23.148341 / 8.074308 (15.074033) | 23.321125 / 10.191392 (13.129733) | 0.245391 / 0.680424 (-0.435032) | 0.031911 / 0.534201 (-0.502290) | 0.470707 / 0.579283 (-0.108576) | 0.608195 / 0.434364 (0.173832) | 0.559590 / 0.540337 (0.019253) | 0.786007 / 1.386936 (-0.600929) |

</details>
</details>

![](https://cml.dev/watermark.png#8e071f565cc0801f73f7f34fba92dc30a43946a9 "CML watermark")
 <details>
<summary>Show benchmarks</summary>

PyArrow==8.0.0

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.008428 / 0.011353 (-0.002925) | 0.004064 / 0.011008 (-0.006944) | 0.088421 / 0.038508 (0.049913) | 0.078042 / 0.023109 (0.054933) | 0.306356 / 0.275898 (0.030458) | 0.349766 / 0.323480 (0.026286) | 0.004086 / 0.007986 (-0.003900) | 0.003900 / 0.004328 (-0.000428) | 0.068379 / 0.004250 (0.064129) | 0.056214 / 0.037052 (0.019161) | 0.310211 / 0.258489 (0.051722) | 0.363692 / 0.293841 (0.069851) | 0.050421 / 0.128546 (-0.078125) | 0.011661 / 0.075646 (-0.063985) | 0.298400 / 0.419271 (-0.120871) | 0.063503 / 0.043533 (0.019970) | 0.339799 / 0.255139 (0.084660) | 0.359479 / 0.283200 (0.076279) | 0.039265 / 0.141683 (-0.102418) | 1.390578 / 1.452155 (-0.061576) | 1.573333 / 1.492716 (0.080617) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.260442 / 0.018006 (0.242436) | 0.560390 / 0.000490 (0.559900) | 0.003926 / 0.000200 (0.003726) | 0.000083 / 0.000054 (0.000029) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.025809 / 0.037411 (-0.011602) | 0.081902 / 0.014526 (0.067376) | 0.093655 / 0.176557 (-0.082901) | 0.149432 / 0.737135 (-0.587703) | 0.099059 / 0.296338 (-0.197279) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.505644 / 0.215209 (0.290435) | 5.108292 / 2.077655 (3.030638) | 2.121689 / 1.504120 (0.617569) | 1.846576 / 1.541195 (0.305381) | 1.836587 / 1.468490 (0.368097) | 0.708088 / 4.584777 (-3.876689) | 4.562630 / 3.745712 (0.816918) | 3.934747 / 5.269862 (-1.335115) | 2.453409 / 4.565676 (-2.112267) | 0.081908 / 0.424275 (-0.342367) | 0.012996 / 0.007607 (0.005389) | 0.636588 / 0.226044 (0.410544) | 6.361086 / 2.268929 (4.092157) | 2.911681 / 55.444624 (-52.532943) | 2.271809 / 6.876477 (-4.604667) | 2.670327 / 2.142072 (0.528254) | 0.943688 / 4.805227 (-3.861539) | 0.191677 / 6.500664 (-6.308988) | 0.066008 / 0.075469 (-0.009461) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.400139 / 1.841788 (-0.441648) | 21.896198 / 8.074308 (13.821890) | 17.853604 / 10.191392 (7.662212) | 0.226603 / 0.680424 (-0.453821) | 0.026682 / 0.534201 (-0.507518) | 0.460131 / 0.579283 (-0.119152) | 0.536790 / 0.434364 (0.102427) | 0.492913 / 0.540337 (-0.047424) | 0.724290 / 1.386936 (-0.662646) |

</details>
PyArrow==latest

<details>
<summary>Show updated benchmarks!</summary>

### Benchmark: benchmark_array_xd.json

| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.007795 / 0.011353 (-0.003557) | 0.009045 / 0.011008 (-0.001963) | 0.085480 / 0.038508 (0.046972) | 0.071881 / 0.023109 (0.048772) | 0.514520 / 0.275898 (0.238622) | 0.569762 / 0.323480 (0.246282) | 0.006126 / 0.007986 (-0.001859) | 0.004153 / 0.004328 (-0.000175) | 0.072150 / 0.004250 (0.067900) | 0.056511 / 0.037052 (0.019458) | 0.484097 / 0.258489 (0.225607) | 0.532673 / 0.293841 (0.238832) | 0.040974 / 0.128546 (-0.087572) | 0.012071 / 0.075646 (-0.063575) | 0.102608 / 0.419271 (-0.316663) | 0.052893 / 0.043533 (0.009360) | 0.485832 / 0.255139 (0.230693) | 0.530479 / 0.283200 (0.247280) | 0.031556 / 0.141683 (-0.110127) | 1.737508 / 1.452155 (0.285354) | 1.834637 / 1.492716 (0.341921) |

### Benchmark: benchmark_getitem\_100B.json

| metric | get_batch_of\_1024\_random_rows | get_batch_of\_1024\_rows | get_first_row | get_last_row |
|--------|---|---|---|---|
| new / old (diff) | 0.423314 / 0.018006 (0.405308) | 0.614163 / 0.000490 (0.613673) | 0.052784 / 0.000200 (0.052584) | 0.000206 / 0.000054 (0.000151) |

### Benchmark: benchmark_indices_mapping.json

| metric | select | shard | shuffle | sort | train_test_split |
|--------|---|---|---|---|---|
| new / old (diff) | 0.031728 / 0.037411 (-0.005684) | 0.088048 / 0.014526 (0.073522) | 0.105759 / 0.176557 (-0.070798) | 0.181433 / 0.737135 (-0.555703) | 0.103133 / 0.296338 (-0.193205) |

### Benchmark: benchmark_iterating.json

| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |
|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 0.659710 / 0.215209 (0.444501) | 5.876378 / 2.077655 (3.798723) | 2.899444 / 1.504120 (1.395324) | 2.871592 / 1.541195 (1.330397) | 2.861205 / 1.468490 (1.392715) | 0.879452 / 4.584777 (-3.705325) | 5.395988 / 3.745712 (1.650275) | 4.548359 / 5.269862 (-0.721502) | 2.946601 / 4.565676 (-1.619076) | 0.099832 / 0.424275 (-0.324443) | 0.008958 / 0.007607 (0.001351) | 0.778480 / 0.226044 (0.552435) | 7.672282 / 2.268929 (5.403354) | 3.963701 / 55.444624 (-51.480923) | 3.154950 / 6.876477 (-3.721527) | 3.351070 / 2.142072 (1.208997) | 1.059459 / 4.805227 (-3.745768) | 0.212035 / 6.500664 (-6.288629) | 0.076941 / 0.075469 (0.001472) |

### Benchmark: benchmark_map_filter.json

| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |
|--------|---|---|---|---|---|---|---|---|---|
| new / old (diff) | 1.639813 / 1.841788 (-0.201975) | 24.807517 / 8.074308 (16.733208) | 20.662500 / 10.191392 (10.471108) | 0.244486 / 0.680424 (-0.435937) | 0.032335 / 0.534201 (-0.501866) | 0.470896 / 0.579283 (-0.108387) | 0.581561 / 0.434364 (0.147197) | 0.495158 / 0.540337 (-0.045179) | 0.788350 / 1.386936 (-0.598586) |

</details>
</details>

![](https://cml.dev/watermark.png#99641ced2e08a28cb876f483babcdd43f7dd76d2 "CML watermark")

Fix #6225 