PHPのPythonスクリプト

Question

私はPHPファイルからPythonスクリプトを実行しています。非常に簡単な例として、完全に動作します。ここではPythonスクリプトは次のとおりです。

#!/usr/bin/env python 

def test(): 
    x = 2 + 1 
    print x + 4 
    return x 

print test() 

そしてPHPスクリプト：

残念ながら

<?php 
    $command = escapeshellcmd('/usr/bin/python2.7 /home/super/PycharmProjects/img_plus_text/helloworld.py'); 
    $output = shell_exec($command); 
    echo $output; 
    echo "Finishing....!"; 
?> 

、より複雑なスクリプトのために、それは動作しません。 1：：/ホーム/スーパー/ binに/カフェ-NV /パイソン：パーミッション拒否されました。ここのPythonスクリプト

#!/usr/bin/env python 

import numpy as np 
import os 
import random 

import caffe 
import cv2 
from sklearn.externals import joblib 

import create_dataset_final_mlp 
import text_2_bow 




def create_class_mapping(): 
    with open("text_processing/encoded-classes.txt") as class_file: 
     lines = class_file.readlines() 
     dictionary = {} 
     for item in lines: 
      item = item.split(" ") 
      dictionary[item[0]] = item[1].replace("\n", "").replace("@", "") 
     return dictionary 


def get_top5(probability_list): 
    result = [] 
    probabilities = [] 
    for i in range(0, 5): 
     top = probability_list.index(max(probability_list)) 
     probabilities.insert(i, probability_list[top]) 
     probability_list[top] = -1 
     result.insert(i, top) 
    return result, probabilities 


def select_random_file(base_dir): 
    # Select random category 
    file_chosen = random.choice(os.listdir(base_dir)) 
    # Select random file in that category 
    file_chosen = random.choice(os.listdir(base_dir + "/" + file_chosen)) 
    return file_chosen 


def get_top5_class_name(mapping, top5_list): 
    class_name_list = [] 
    for i in range(0, 5): 
     index = top5_list[i] 
     class_name = mapping[str(index)] 
     class_name_list.insert(i, class_name) 
    return class_name_list 


def main(image_to_classify): 
    dataset_path = "/images-test1" 
    image_file_chosen = create_dataset_final_mlp.find(image_to_classify, dataset_path) 

    if image_file_chosen is None: 
     image_file_chosen = select_random_file("%s" % dataset_path) 

    identifier = image_file_chosen.split(".")[0] 
    print "Identifier: " + identifier 

    dictionary = text_2_bow.create_dictionary("text_processing/dictionary-1000-words.csv") 

    # load CNN model from disk 
    classifier = create_dataset_final_mlp.load_model_from_disk("test/deploy.prototxt", 
                   "test/snapshot_iter_1020.caffemodel", '256,256', 
                   "test/converted_mean.npy") 

    # load the final MLP to classify patterns 
    print "loading model from disk..." 
    mlp = joblib.load("trained_model_9097_5000_3000_iter_100.model") 

    with open("export-ferramenta.csv") as export_file: 
     for line in export_file: 
      if identifier in line: 
       pattern = line 
       print "Pattern: " + pattern 
       break 

    # Show selected image 
    full_img_path = create_dataset_final_mlp.find(image_file_chosen, dataset_path) 
    # img = cv2.imread(full_img_path, cv2.IMREAD_COLOR) 
    # cv2.imshow("Image selected", img) 
    # cv2.waitKey(0) 

    # get the CNN features 
    inputs = [caffe.io.load_image(full_img_path)] 
    # the second parameter is used to switch for prediction from center crop alone instead of averaging predictions across crops (default). 
    classifier.predict(inputs, False) 
    features = classifier.blobs['fc6'].data[0] 
    extracted_cnn_features = create_dataset_final_mlp.get_cnn_features_as_vector(features) 
    extracted_cnn_features = extracted_cnn_features[:-1] 
    extracted_cnn_features = extracted_cnn_features.split(",") 

    # transform the text using text_2_bow functions 
    pattern = pattern.split(",") 
    text_pattern = pattern[1] + pattern[2] 
    matrix = text_2_bow.get_matrix(text_pattern, dictionary) 
    reshaped_matrix = np.reshape(matrix, 5000).tolist() 

    full_features_vector = extracted_cnn_features + reshaped_matrix 
    full_features_vector = np.asarray(full_features_vector, np.float64) 

    # use the MLP to classify 
    prediction = mlp.predict_proba([full_features_vector]) 
    tolist = prediction[0].tolist() 

    mapping = create_class_mapping() 
    top5, probabilities = get_top5(tolist) 
    top_class_name = get_top5_class_name(mapping, top5) 

    print "Top 5 classes: ", top_class_name 
    print "Top 5 probs ", probabilities 
    return top_class_name, probabilities 


if __name__ == "__main__": 
    main("") 

PHPスクリプト

<?php 

echo exec('sudo /home/super/bin/caffe-nv/python /home/super/PycharmProjects/img_plus_text/demo_website.py 2>&1'); 

?> 

ERROR

shがあります

私はthしかし、私はここで立ち往生しています。間違いを指摘してください。ありがとうございました。

Answer 1

問題は、環境変数とした

export LD_LIBRARY_PATH=/usr/lib/x86_64-linux-gnu/:$LD_LIBRARY_PATH 
export PYTHONPATH=$PYTHONPATH:/home/super/bin/caffe-nv/python/ 
python /demo_website2.py $1 

以下のように、私はその後、私は「それは動作しません」exec

exec("/opt/lampp/htdocs/test/run.sh ". $param, $output);