<jupyter_start><jupyter_text>Output<jupyter_code>fig = plt.figure(figsize=(15, 10))

dil = dilation(img)
fig.add_subplot(121)
plt.imshow(dil, cmap="gray")
plt.title("Dilation")

ero = erosion(img)
fig.add_subplot(122)
plt.imshow(ero, cmap="gray")
plt.title("Erosion")

plt.show()
replace(dil)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.18322981366459629, 'fraction_numerical': 0.031055900621118012, 'mean_word_length': 9.419354838709678, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '487411', 'license': 'MIT', 'n_tokens_mistral': 158, 'n_tokens_neox': 139, 'n_words': 17, 'path': 'all final/Dilation and Erosion.ipynb', 'repo_name': 'parthjain98in/image-processing', 'size': '322'}