| import requests |
| import json |
| from datetime import date, datetime, timedelta |
| import os |
|
|
| from typing import Optional, Dict, Union, List |
|
|
|
|
| def keywords(content: str=None, url: str='http://image.everypixel.com/2014.12/67439828186edc79b9be81a4dedea8b03c09a12825b_b.jpg', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): |
| """ |
| "By sending an image to this method you can get a list of suggested keywords. You may specify a number of returned words or a threshold of its minimum score. Just provide num_keywords or threshold parameter to this method." |
| content: You can also send an actual image files for auto-tagging. |
| url: Image URL to perform auto-tagging on. |
| |
| """ |
| url = f"https://everypixel-api.p.rapidapi.com/keywords" |
| querystring = {} |
| if content: |
| querystring['content'] = content |
| if url: |
| querystring['url'] = url |
| |
| headers = { |
| "X-RapidAPI-Key": toolbench_rapidapi_key, |
| "X-RapidAPI-Host": "everypixel-api.p.rapidapi.com" |
| } |
|
|
|
|
| response = requests.get(url, headers=headers, params=querystring) |
| try: |
| observation = response.json() |
| except: |
| observation = response.text |
| return observation |
|
|
| def quality_ugc(content: str=None, url: str='http://image.everypixel.com/2014.12/67439828186edc79b9be81a4dedea8b03c09a12825b_b.jpg', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): |
| """ |
| "The main difference between Stock photo scoring and this model is in the training dataset. User-Generated Photo Scoring is a model trained on a 347 000 of user photos from Instagram. Estimation parameters for this model were prepared by a group of 10 professional photographers. Scoring methods are based on five classes: very bad (0-20), bad (20-40), normal (40-60), good (60-80) and excellent (80-100). This model is designed to evaluate user photos taken both by a professional camera and by a camera of a smartphone. It doesn't estimate the plot and do not measure how cool or beautiful a person or an object on a photo may look. It cares only about technical parts like brightness, contrast, noise and so on. The service is not dedicated for scoring historical photos, illustrations or 3D visualizations." |
| content: You can also send an actual image files for scoring. |
| url: Image URL to perform scoring on. |
| |
| """ |
| url = f"https://everypixel-api.p.rapidapi.com/quality_ugc" |
| querystring = {} |
| if content: |
| querystring['content'] = content |
| if url: |
| querystring['url'] = url |
| |
| headers = { |
| "X-RapidAPI-Key": toolbench_rapidapi_key, |
| "X-RapidAPI-Host": "everypixel-api.p.rapidapi.com" |
| } |
|
|
|
|
| response = requests.get(url, headers=headers, params=querystring) |
| try: |
| observation = response.json() |
| except: |
| observation = response.text |
| return observation |
|
|
| def quality(content: str=None, url: str='http://image.everypixel.com/2014.12/67439828186edc79b9be81a4dedea8b03c09a12825b_b.jpg', toolbench_rapidapi_key: str='088440d910mshef857391f2fc461p17ae9ejsnaebc918926ff'): |
| """ |
| "This method allows you to get the quality score for your photo. This service doesn't measure how cool or beautiful a person or an object on a photo may look. It cares only about technical parts like brightness, contrast, noise and so on. The service is not dedicated for scoring historical photos, illustrations or 3D visualizations." |
| content: You can also send an actual image files for scoring. |
| url: Image URL to perform scoring on. |
| |
| """ |
| url = f"https://everypixel-api.p.rapidapi.com/quality" |
| querystring = {} |
| if content: |
| querystring['content'] = content |
| if url: |
| querystring['url'] = url |
| |
| headers = { |
| "X-RapidAPI-Key": toolbench_rapidapi_key, |
| "X-RapidAPI-Host": "everypixel-api.p.rapidapi.com" |
| } |
|
|
|
|
| response = requests.get(url, headers=headers, params=querystring) |
| try: |
| observation = response.json() |
| except: |
| observation = response.text |
| return observation |
|
|
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|
