<jupyter_start><jupyter_text>upload and find the emotion of the person in the pic<jupyter_code>!pip install paralleldots
import paralleldots
paralleldots.set_api_key("I aint giving you my API key get yours from ParallelDots")

from google.colab import files
files.upload()
CONTENT_IMAGE = "angry-little-girl.jpg"
path= "/content/"+CONTENT_IMAGE
print( paralleldots.facial_emotion( path ) )
result = paralleldots.facial_emotion( path )
print(result)
mood = result['facial_emotion'][0]['tag']<jupyter_output><empty_output><jupyter_text>Printing only the most accurate emotion<jupyter_code>print(mood)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.10191082802547771, 'fraction_numerical': 0.0015923566878980893, 'mean_word_length': 8.530303030303031, 'pattern_counts': {'":': 0, '<': 9, '<?xml version=': 0, '>': 9, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '111063', 'license': 'Unlicense', 'n_tokens_mistral': 219, 'n_tokens_neox': 209, 'n_words': 49, 'path': 'Emotion.ipynb', 'repo_name': 'zszazi/awesome-collection-of-google-colab-notebooks', 'size': '628'}