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Inference not working after a training with convert_to_grayscale: true #6201

Closed mshtmfv closed 4 years ago

mshtmfv commented 5 years ago

System information

Describe the problem

Have problem with convert_to_grayscale parameter in pipeline.config when trying to inference on frozen graph.

Source code / logs

InvalidArgumentError: PartialTensorShape: Incompatible shapes during merge: [1,1,1] vs. [640,640,1] [[node Preprocessor/map/TensorArrayStack/TensorArrayGatherV3 (defined at <ipython-input-363-81ec5e7b9a34>:7) = TensorArrayGatherV3[dtype=DT_FLOAT, element_shape=[640,640,1], _device="/job:localhost/replica:0/task:0/device:CPU:0"](Preprocessor/map/TensorArray_1, Preprocessor/map/TensorArrayStack/range, Preprocessor/map/while/Exit_2)]]

My config file:

# SSD with Resnet 50 v1 FPN feature extractor, shared box predictor and focal
# loss (a.k.a Retinanet).
# See Lin et al, https://arxiv.org/abs/1708.02002
# Trained on COCO, initialized from Imagenet classification checkpoint

# Achieves 35.2 mAP on COCO14 minival dataset. Doubling the number of training
# steps to 50k gets 36.9 mAP

# This config is TPU compatible

model {
  ssd {
    inplace_batchnorm_update: true
    freeze_batchnorm: false
    num_classes: 14
    box_coder {
      faster_rcnn_box_coder {
        y_scale: 10.0
        x_scale: 10.0
        height_scale: 5.0
        width_scale: 5.0
      }
    }
    matcher {
      argmax_matcher {
        matched_threshold: 0.5
        unmatched_threshold: 0.5
        ignore_thresholds: false
        negatives_lower_than_unmatched: true
        force_match_for_each_row: true
        use_matmul_gather: true
      }
    }
    similarity_calculator {
      iou_similarity {
      }
    }
    encode_background_as_zeros: true
    anchor_generator {
      multiscale_anchor_generator {
        min_level: 3
        max_level: 7
        anchor_scale: 4.0
        aspect_ratios: [1.0, 2.0, 0.5]
        scales_per_octave: 2
      }
    }
    image_resizer {
      fixed_shape_resizer {
        height: 640
        width: 640
        convert_to_grayscale: true
      }
    }
    box_predictor {
      weight_shared_convolutional_box_predictor {
        depth: 256
        class_prediction_bias_init: -4.6
        conv_hyperparams {
          activation: RELU_6,
          regularizer {
            l2_regularizer {
              weight: 0.000004
            }
          }
          initializer {
            random_normal_initializer {
              stddev: 0.01
              mean: 0.0
            }
          }
          batch_norm {
            scale: true,
            decay: 0.997,
            epsilon: 0.001,
          }
        }
        num_layers_before_predictor: 4
        kernel_size: 3
      }
    }
    feature_extractor {
      type: 'ssd_resnet50_v1_fpn'
      fpn {
        min_level: 3
        max_level: 7
      }
      min_depth: 16
      depth_multiplier: 1.0
      conv_hyperparams {
        activation: RELU_6,
        regularizer {
          l2_regularizer {
            weight: 0.000004
          }
        }
        initializer {
          truncated_normal_initializer {
            stddev: 0.03
            mean: 0.0
          }
        }
        batch_norm {
          scale: true,
          decay: 0.997,
          epsilon: 0.001,
        }
      }
      override_base_feature_extractor_hyperparams: true
    }
    loss {
      classification_loss {
        weighted_sigmoid_focal {
          alpha: 0.25
          gamma: 2.0
        }
      }
      localization_loss {
        weighted_smooth_l1 {
        }
      }
      classification_weight: 2.0
      localization_weight: 1.0
    }
    normalize_loss_by_num_matches: true
    normalize_loc_loss_by_codesize: true
    post_processing {
      batch_non_max_suppression {
        score_threshold: 0.1
        iou_threshold: 0.6
        max_detections_per_class: 100
        max_total_detections: 100
      }
      score_converter: SIGMOID
    }
  }
}

train_config: {
  fine_tune_checkpoint: "/workspace/ssd_resnet50_v1_fpn_shared_box_predictor_640x640_coco14_sync_2018_07_03/model.ckpt"
  from_detection_checkpoint: true
  batch_size: 8
  sync_replicas: true
  startup_delay_steps: 0
  replicas_to_aggregate: 8
  num_steps: 2000000
  data_augmentation_options {
    random_horizontal_flip {
    }
  }
  data_augmentation_options {
    random_crop_image {
      min_object_covered: 0.0
      min_aspect_ratio: 0.75
      max_aspect_ratio: 3.0
      min_area: 0.75
      max_area: 1.0
      overlap_thresh: 0.0
    }
  }
  optimizer {
   momentum_optimizer {
      learning_rate {
        manual_step_learning_rate {
          initial_learning_rate: 0.005
          schedule {
            step: 50000
            learning_rate: 0.0005
          }
          schedule {
            step: 100000
            learning_rate: 0.00005
          }
        }
      }
      momentum_optimizer_value: 0.899999976158
    }
    use_moving_average: false
  }
  max_number_of_boxes: 100
  unpad_groundtruth_tensors: false
}
train_input_reader {
  label_map_path: "/workspace/label_map.pbtxt"
  tf_record_input_reader {
    input_path: "/workspace/data_train_shuffle/train.record-?????-of-00100"
  }
}
eval_config {
  num_examples: 3000
  max_evals: 10
  use_moving_averages: false
}
eval_input_reader {
  label_map_path: "/workspace/label_map.pbtxt"
  shuffle: false
  num_readers: 1
  tf_record_input_reader {
    input_path: "/workspace/eval-dataset.tfrecords"
  }
}
tensorflowbutler commented 4 years ago

Hi There, We are checking to see if you still need help on this, as this seems to be an old issue. Please update this issue with the latest information, code snippet to reproduce your issue and error you are seeing. If we don't hear from you in the next 7 days, this issue will be closed automatically. If you don't need help on this issue any more, please consider closing this.