TensorFlow Hub Rilevamento di oggetti Colab

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Benvenuto nel TensorFlow Hub Object Detection Colab! Questo taccuino ti guiderà attraverso i passaggi per eseguire un modello di rilevamento degli oggetti "pronto all'uso" sulle immagini.

Più modelli

Questa raccolta contiene modelli TF 2 di rilevamento di oggetti che sono stati addestrati sul COCO 2.017 set di dati. Qui si possono trovare tutti i modelli di rilevamento di oggetti che sono attualmente ospitati in tfhub.dev .

Importazioni e configurazione

Cominciamo con le importazioni di base.

# This Colab requires TF 2.5.
pip install -U tensorflow>=2.5
import os
import pathlib

import matplotlib
import matplotlib.pyplot as plt

import io
import scipy.misc
import numpy as np
from six import BytesIO
from PIL import Image, ImageDraw, ImageFont
from six.moves.urllib.request import urlopen

import tensorflow as tf
import tensorflow_hub as hub

tf.get_logger().setLevel('ERROR')
2021-07-29 12:46:47.920264: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0

Utilità

Esegui la cella seguente per creare alcuni programmi di utilità che saranno necessari in seguito:

  • Metodo di supporto per caricare un'immagine
  • Mappa del nome del modello sull'impugnatura dell'hub TF
  • Elenco delle tuple con Human Keypoints per il set di dati COCO 2017. Questo è necessario per i modelli con punti chiave.

Strumenti di visualizzazione

Per visualizzare le immagini con i riquadri, i punti chiave e la segmentazione corretti rilevati, utilizzeremo l'API TensorFlow Object Detection. Per installarlo cloneremo il repository.

# Clone the tensorflow models repository
git clone --depth 1 https://github.com/tensorflow/models
Cloning into 'models'...
remote: Enumerating objects: 2811, done.[K
remote: Counting objects: 100% (2811/2811), done.[K
remote: Compressing objects: 100% (2348/2348), done.[K
remote: Total 2811 (delta 720), reused 1326 (delta 427), pack-reused 0[K
Receiving objects: 100% (2811/2811), 32.80 MiB | 25.14 MiB/s, done.
Resolving deltas: 100% (720/720), done.

Installazione dell'API di rilevamento degli oggetti

sudo apt install -y protobuf-compiler
cd models/research/
protoc object_detection/protos/*.proto --python_out=.
cp object_detection/packages/tf2/setup.py .
python -m pip install .

Ora possiamo importare le dipendenze di cui avremo bisogno in seguito

from object_detection.utils import label_map_util
from object_detection.utils import visualization_utils as viz_utils
from object_detection.utils import ops as utils_ops

%matplotlib inline

Caricare i dati della mappa dell'etichetta (per la stampa).

Mappe Label corrispondono numeri indice di nomi di categoria, in modo che quando la nostra rete circonvoluzione prevede 5 , sappiamo che questo corrisponde ad airplane . Qui usiamo funzioni di utilità interne, ma tutto ciò che restituisce un dizionario che mappa interi alle etichette di stringa appropriate andrebbe bene.

Stiamo andando, per semplicità, a caricare dal repository che abbiamo caricato il codice dell'API Object Detection

PATH_TO_LABELS = './models/research/object_detection/data/mscoco_label_map.pbtxt'
category_index = label_map_util.create_category_index_from_labelmap(PATH_TO_LABELS, use_display_name=True)

Crea un modello di rilevamento e carica i pesi del modello pre-addestrati

Qui sceglieremo quale modello di rilevamento oggetti utilizzeremo. Seleziona l'architettura e verrà caricata automaticamente. Se vuoi cambiare il modello per provare altre architetture in un secondo momento, cambia semplicemente la cella successiva ed esegui le seguenti.

Suggerimento: se si desidera leggere ulteriori dettagli circa il modello selezionato, è possibile seguire il link (maniglia modello) e leggere ulteriore documentazione sul TF Hub. Dopo aver selezionato un modello, stamperemo la maniglia per renderlo più semplice.

Selezione del modello

Selected model:CenterNet HourGlass104 Keypoints 512x512
Model Handle at TensorFlow Hub: https://tfhub.dev/tensorflow/centernet/hourglass_512x512_kpts/1

Caricamento del modello selezionato da TensorFlow Hub

Qui abbiamo solo bisogno dell'handle del modello che è stato selezionato e utilizziamo la libreria Tensorflow Hub per caricarlo in memoria.

print('loading model...')
hub_model = hub.load(model_handle)
print('model loaded!')
loading model...
2021-07-29 12:47:58.250660: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcuda.so.1
2021-07-29 12:47:58.902318: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.903211: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties: 
pciBusID: 0000:00:05.0 name: Tesla V100-SXM2-16GB computeCapability: 7.0
coreClock: 1.53GHz coreCount: 80 deviceMemorySize: 15.78GiB deviceMemoryBandwidth: 836.37GiB/s
2021-07-29 12:47:58.903258: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0
2021-07-29 12:47:58.907111: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11
2021-07-29 12:47:58.907220: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11
2021-07-29 12:47:58.908416: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcufft.so.10
2021-07-29 12:47:58.908804: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcurand.so.10
2021-07-29 12:47:58.909937: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusolver.so.11
2021-07-29 12:47:58.910898: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcusparse.so.11
2021-07-29 12:47:58.911133: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8
2021-07-29 12:47:58.911272: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.912260: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.913201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0
2021-07-29 12:47:58.913915: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 AVX512F FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-07-29 12:47:58.914543: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.915462: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1733] Found device 0 with properties: 
pciBusID: 0000:00:05.0 name: Tesla V100-SXM2-16GB computeCapability: 7.0
coreClock: 1.53GHz coreCount: 80 deviceMemorySize: 15.78GiB deviceMemoryBandwidth: 836.37GiB/s
2021-07-29 12:47:58.915573: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.916522: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:58.917369: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1871] Adding visible gpu devices: 0
2021-07-29 12:47:58.917413: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudart.so.11.0
2021-07-29 12:47:59.515621: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1258] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-07-29 12:47:59.515661: I tensorflow/core/common_runtime/gpu/gpu_device.WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_42408) with ops with custom gradients. Will likely fail if a gradient is requested.
cc:1264]      0 
2021-07-29 12:47:59.515671: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1277] 0:   N 
2021-07-29 12:47:59.515963: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:59.516978: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:59.517921: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:937] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2021-07-29 12:47:59.518868: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1418] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 14646 MB memory) -> physical GPU (device: 0, name: Tesla V100-SXM2-16GB, pci bus id: 0000:00:05.0, compute capability: 7.0)
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WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215296) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_206776) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_213256) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_46184) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_221056) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_220816) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_39535) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_206176) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217576) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210736) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_208816) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_220456) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_32333) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_32104) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_53793) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_207136) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_208216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_input_downsample_block_layer_call_and_return_conditional_losses_184458) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_222256) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217096) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_encoder_decoder_block_5_layer_call_and_return_conditional_losses_73080) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215896) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_27667) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_206056) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210976) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210616) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_213496) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_55382) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_34113) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_53100) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_22798) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_21247) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_223936) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_218536) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_29002) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_216856) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_216256) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_207856) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_31659) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217696) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_21463) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_33223) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_54689) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_convolutional_block_72_layer_call_and_return_conditional_losses_66888) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_208456) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_35454) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_208936) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_49960) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_26345) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215056) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_42192) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_41531) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_216736) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_28786) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_220216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_49286) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219136) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_37056) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_22124) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_209656) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_37952) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_21679) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_convolutional_block_36_layer_call_and_return_conditional_losses_203862) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_209056) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_209176) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_25671) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_48625) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_214696) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_214216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_hourglass_network_layer_call_and_return_conditional_losses_158598) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_223816) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_206296) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217336) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215536) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210256) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_41302) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_30553) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_45739) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_29892) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_221296) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_206536) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_211216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_209296) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_47290) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_208336) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_38861) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_222136) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219616) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_51066) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_205936) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215176) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_32778) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_24794) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_212776) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_205456) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_26116) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_212656) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_27006) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_35238) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_23459) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_214936) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_44188) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219736) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_35918) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_51746) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_218656) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_34329) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_34793) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_29663) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_37488) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_46400) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_51282) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210856) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_221656) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_205216) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_30782) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_52191) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219496) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_56043) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_30998) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_222616) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215416) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_220576) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_42853) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_25900) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_214576) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_41086) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_29218) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_53348) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_25010) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_216976) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_40196) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219856) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_211096) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_36147) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_35009) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_54473) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_hourglass_network_layer_call_and_return_conditional_losses_177444) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_217456) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_40641) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_222856) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_48180) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_32549) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_215776) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_219376) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_213136) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_47951) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_39090) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_28341) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_207496) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_33668) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_convolutional_block_72_layer_call_and_return_conditional_losses_204131) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_223456) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_52884) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_encoder_decoder_block_5_layer_call_and_return_conditional_losses_200628) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_223576) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_30337) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_24565) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_210376) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_212296) with ops with custom gradients. Will likely fail if a gradient is requested.
WARNING:absl:Importing a function (__inference_batchnorm_layer_call_and_return_conditional_losses_222376) with ops with custom gradients. Will likely fail if a gradient is requested.
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model loaded!

Caricamento di un'immagine

Proviamo il modello su una semplice immagine. Per aiutare con questo, forniamo un elenco di immagini di prova.

Ecco alcune semplici cose da provare se sei curioso:

  • Prova a eseguire l'inferenza sulle tue immagini, caricale su colab e caricale allo stesso modo nella cella sottostante.
  • Modifica alcune delle immagini in ingresso e verifica se il rilevamento funziona ancora. Alcune semplici cose da provare qui includono il ribaltamento dell'immagine orizzontalmente o la conversione in scala di grigi (nota che ci aspettiamo ancora che l'immagine di input abbia 3 canali).

Attenzione: quando si usano le immagini con un canale alfa, il modello si aspettano 3 immagini canali e l'alfa conterà come un 4 °.

Selezione immagine (non dimenticare di eseguire la cella!)

png

Fare l'inferenza

Per fare l'inferenza dobbiamo solo chiamare il nostro modello caricato TF Hub.

Cose che puoi provare:

  • Stampare result['detection_boxes'] e cercare di abbinare le sedi di dialogo per le caselle nell'immagine. Notare che le coordinate sono date in forma normalizzata (cioè, nell'intervallo [0, 1]).
  • ispezionare altre chiavi di output presenti nel risultato. Una documentazione completa può essere vista nella pagina della documentazione dei modelli (puntando il browser all'handle del modello stampato in precedenza)
# running inference
results = hub_model(image_np)

# different object detection models have additional results
# all of them are explained in the documentation
result = {key:value.numpy() for key,value in results.items()}
print(result.keys())
2021-07-29 12:48:38.049124: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:176] None of the MLIR Optimization Passes are enabled (registered 2)
2021-07-29 12:48:38.178759: I tensorflow/core/platform/profile_utils/cpu_utils.cc:114] CPU Frequency: 2000179999 Hz
2021-07-29 12:48:38.927843: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: StatefulPartitionedCall/cond/then/_918/cond/Assert_2/AssertGuard/branch_executed/_1123
2021-07-29 12:48:40.206597: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcudnn.so.8
2021-07-29 12:48:40.674626: I tensorflow/stream_executor/cuda/cuda_dnn.cc:359] Loaded cuDNN version 8100
2021-07-29 12:48:41.378432: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublas.so.11
2021-07-29 12:48:41.749470: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libcublasLt.so.11
dict_keys(['detection_classes', 'detection_keypoints', 'detection_boxes', 'detection_scores', 'detection_keypoint_scores', 'num_detections'])

Visualizzazione dei risultati

Qui è dove avremo bisogno dell'API TensorFlow Object Detection per mostrare i quadrati dalla fase di inferenza (e i punti chiave quando disponibili).

la documentazione completa di questo metodo può essere visto qui

Qui è possibile, per esempio, insieme min_score_thresh ad altri valori (tra 0 e 1) per consentire a più rilevamenti o per filtrare più rilevamenti.

label_id_offset = 0
image_np_with_detections = image_np.copy()

# Use keypoints if available in detections
keypoints, keypoint_scores = None, None
if 'detection_keypoints' in result:
  keypoints = result['detection_keypoints'][0]
  keypoint_scores = result['detection_keypoint_scores'][0]

viz_utils.visualize_boxes_and_labels_on_image_array(
      image_np_with_detections[0],
      result['detection_boxes'][0],
      (result['detection_classes'][0] + label_id_offset).astype(int),
      result['detection_scores'][0],
      category_index,
      use_normalized_coordinates=True,
      max_boxes_to_draw=200,
      min_score_thresh=.30,
      agnostic_mode=False,
      keypoints=keypoints,
      keypoint_scores=keypoint_scores,
      keypoint_edges=COCO17_HUMAN_POSE_KEYPOINTS)

plt.figure(figsize=(24,32))
plt.imshow(image_np_with_detections[0])
plt.show()

png

[Opzionale]

Tra i modelli di rilevamento degli oggetti disponibili c'è Mask R-CNN e l'output di questo modello consente la segmentazione dell'istanza.

Per visualizzarlo useremo lo stesso metodo che abbiamo fatto prima, ma l'aggiunta di un parametro di adizionale: instance_masks=output_dict.get('detection_masks_reframed', None)

# Handle models with masks:
image_np_with_mask = image_np.copy()

if 'detection_masks' in result:
  # we need to convert np.arrays to tensors
  detection_masks = tf.convert_to_tensor(result['detection_masks'][0])
  detection_boxes = tf.convert_to_tensor(result['detection_boxes'][0])

  # Reframe the the bbox mask to the image size.
  detection_masks_reframed = utils_ops.reframe_box_masks_to_image_masks(
            detection_masks, detection_boxes,
              image_np.shape[1], image_np.shape[2])
  detection_masks_reframed = tf.cast(detection_masks_reframed > 0.5,
                                      tf.uint8)
  result['detection_masks_reframed'] = detection_masks_reframed.numpy()

viz_utils.visualize_boxes_and_labels_on_image_array(
      image_np_with_mask[0],
      result['detection_boxes'][0],
      (result['detection_classes'][0] + label_id_offset).astype(int),
      result['detection_scores'][0],
      category_index,
      use_normalized_coordinates=True,
      max_boxes_to_draw=200,
      min_score_thresh=.30,
      agnostic_mode=False,
      instance_masks=result.get('detection_masks_reframed', None),
      line_thickness=8)

plt.figure(figsize=(24,32))
plt.imshow(image_np_with_mask[0])
plt.show()

png