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| import streamlit as st | |
| import numpy as np | |
| import PIL.Image | |
| import base64 | |
| from io import BytesIO | |
| import os | |
| import requests | |
| import urllib.request | |
| st.write("This app generates photos with the DALL-E Encoder. \n \n To use this app, simply upload a photo and click 'Generate'. \n \n This app is in Alpha so please be patient with it.") | |
| st.title("Photo Editor V1.0") | |
| def generate_image(image_path): | |
| image = load_image(image_path) | |
| st.image(image, use_column_width=True, caption="Original Image") | |
| st.write("Generated image:") | |
| generated_image = inpaint_image(image_path) | |
| st.image(generated_image, use_column_width=True, caption="Generated Image") | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| # st.write("Generated image:") | |
| # generated_image = inpaint_image(image) | |
| # st.image(generated_image, use_column_width=True) | |
| def load_image(image_path): | |
| image = PIL.Image.open(image_path) | |
| return np.array(image) | |
| def inpaint_image(image_path): | |
| # image = PIL.Image.fromarray(image) | |
| # buffered = BytesIO() | |
| # image.save(buffered, format="JPEG") | |
| # encoded_image = base64.b64encode(buffered.getvalue()).decode("utf-8") | |
| # response = requests.post( | |
| # "https://api.deepai.org/api/inpaint", | |
| # data={ | |
| # "image": encoded_image, | |
| # "filename": "image.jpg", | |
| # }, | |
| # headers={ | |
| # "api-key": API_KEY, | |
| # }, | |
| # ) | |
| # if response.status_code == 200: | |
| # response_json = response.json() | |
| # output_url = response_json["output_url"] | |
| # response = requests.get(output_url) | |
| # image = PIL.Image.open(BytesIO(response.content)) | |
| # return np.array(image) | |
| # else: | |
| # st.error("Something went wrong. Please try again.") | |
| url = "https://api.andersonrobotics.com/api/v1/generate" | |
| payload = { | |
| "prompt": "a boy and a girl are playing with a ball and a cat and a dog", | |
| "num_samples": 1, | |
| "num_return": 1, | |
| "temperature": 1.0, | |
| "top_k": 0, | |
| "top_p": 0.0, | |
| "model_name": "dall-e" | |
| } | |
| files = [ | |
| ('file', open(image_path, 'rb')) | |
| ] | |
| headers = { | |
| 'Authorization': "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJ1c2VybmFtZSI6ImFkbWluIiwiZW1haWwiOiJhZG1pbkBhbmRlcnNvbnJvY2tldGljcy5jb20iLCJpYXQiOjE1OTYxNzE1MjB9.nHpKW8eNvfZQQbzDmwq7WjzvfzgT9T6DlL-YW8Fv1Zs" | |
| } | |
| response = requests.request("POST", url, headers=headers, data = payload, files = files) | |
| print(response.text.encode('utf8')) | |
| image_url = response.json()["data"][0]["image"] | |
| urllib.request.urlretrieve(image_url, "image.png") | |
| image = load_image("image.png") | |
| return image | |
| image_file = st.file_uploader("Upload an image", type=['jpg', 'png', 'jpeg']) | |
| if image_file is not None: | |
| generate_image(image_file) |