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name: "ResNet-50" | |
layer { | |
name: 'input-data' | |
type: 'Python' | |
top: 'data' | |
top: 'im_info' | |
top: 'gt_boxes' | |
python_param { | |
module: 'roi_data_layer.layer' | |
layer: 'RoIDataLayer' |
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name: "RESNET_Mask-RCNN" | |
input: "data" | |
input_dim: 1 | |
input_dim: 3 | |
input_dim: 224 | |
input_dim: 224 | |
input: "rois" | |
input_dim: 1 # to be changed on-the-fly to num ROIs |
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import math | |
import pandas as pd | |
shots = pd.read_csv('shots.csv') | |
faces = pd.read_csv('face_result.csv') | |
significant_scenes = [] | |
for idx, row in shots.iterrows(): | |
frames = list(range( | |
int(round(row['begin'])), |
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import csv | |
import io | |
import os | |
from google.cloud import vision | |
def detect_faces(path): | |
client = vision.ImageAnnotatorClient() |
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<p>This is the translation</p> |
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<p>This is the translation</p> |
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<p>This is the translation</p> |
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hello |
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<p>This is the translation</p> |
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<p>This is the translation</p> |
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