45 lines
2.0 KiB
Markdown
45 lines
2.0 KiB
Markdown
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# How to expand batch for use multi-batch function
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## Model Source
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The model used in this example come from the following open source projects:
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https://github.com/shicai/MobileNet-Caffe
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## Script Usage
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*Usage:*
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```
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python test.py
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```
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*Description:*
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- The default target platform in script is 'rk3566', please modify the 'target_platform' parameter of 'rknn.config' according to the actual platform.
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- If connecting board is required, pl'ease add the 'target' parameter in 'rknn.init_runtime'.
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- You can modify the 'rknn_batch_size' parameter of 'rknn.build' to achieve the effect of multi-batch.
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## Expected Results
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This example will print the TOP5 labels and corresponding scores of the test image classification results for every batch, as follows:
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```
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----- Batch 0: TOP 5 -----
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[155] score:0.993652 class:"Shih-Tzu"
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[154] score:0.002834 class:"Pekinese, Pekingese, Peke"
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[204] score:0.002172 class:"Lhasa, Lhasa apso"
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[283] score:0.000571 class:"Persian cat"
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[284] score:0.000133 class:"Siamese cat, Siamese"
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----- Batch 1: TOP 5 -----
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[ 1] score:0.598145 class:"goldfish, Carassius auratus"
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[794] score:0.062073 class:"shower curtain"
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[996] score:0.062073 class:"hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa"
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[927] score:0.041687 class:"trifle"
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[115] score:0.027863 class:"sea slug, nudibranch"
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----- Batch 2: TOP 5 -----
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[812] score:0.999023 class:"space shuttle"
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[148] score:0.000293 class:"killer whale, killer, orca, grampus, sea wolf, Orcinus orca"
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[517] score:0.000132 class:"crane"
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[833] score:0.000132 class:"submarine, pigboat, sub, U-boat"
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[525] score:0.000089 class:"dam, dike, dyke"
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----- Batch 3: TOP 5 -----
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[155] score:0.993652 class:"Shih-Tzu"
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[154] score:0.002834 class:"Pekinese, Pekingese, Peke"
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[204] score:0.002172 class:"Lhasa, Lhasa apso"
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[283] score:0.000571 class:"Persian cat"
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[284] score:0.000133 class:"Siamese cat, Siamese"
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```
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- Note: Different platforms, different versions of tools and drivers may have slightly different results.
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