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color_palette.py

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+import vertexai
+from vertexai.generative_models import GenerativeModel, Image
+# import streamlit as st
+import os 
+
+PROJECT_ID = "agileai-poc"
+REGION = "us-central1"
+vertexai.init(project=PROJECT_ID, location=REGION)
+# upload_image = st.file_uploader("Upload an image", type=["jpeg","png","jpg"],accept_multiple_files=True)
+# print(upload_image)
+IMAGE_FILE = "/home/lenovo/Pictures/palette_samples/3.jpg"
+image = Image.load_from_file(IMAGE_FILE)
+# if upload_image:
+#     image = Image.load_from_file(upload_image)
+
+generative_multimodal_model = GenerativeModel("gemini-1.0-pro-vision")
+prompt=""""  Describe the desired theme,or brand,mood,and palette,detect objects and generate the appealing color palettes on image with respective object and rgb code "
+output format should be "object name :rgb code"
+
+example:
+tree leaf: (0,255,0)
+pillow :(12,0,230)
+"""
+prompt2=""""  Describe the desired theme,or brand,mood,and palette,detect objects with 100 percent accuracy and generate the appealing color palettes on image with respective object ,color name and hexacode "
+output format should be "object name : color :hexacode"
+
+example:
+object_name :color :(hexacode)
+"""
+
+# print("\n RGB ************************************** \n")
+# response1 = generative_multimodal_model.generate_content([prompt, image])
+# print(response1.text)
+print("\n hexacode ************************************** \n")
+response2 = generative_multimodal_model.generate_content([prompt2, image])
+print(response2.text)

image.py

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+import vertexai
+from vertexai.generative_models import GenerativeModel, Image
+import streamlit as st
+import os 
+# export STREAMLIT_SERVER_MAX_UPLOAD_SIZE=200
+PROJECT_ID = "agileai-poc"
+REGION = "us-central1"
+vertexai.init(project=PROJECT_ID, location=REGION)
+# upload_image = st.file_uploader("Upload an image", type=["jpeg","png","jpg"],accept_multiple_files=True)
+# print(upload_image)
+# IMAGE_FILE = "image-path"
+image =st.file_uploader("upload file",type=["png","jpg","jpeg"],accept_multiple_files=True)
+# if file:
+#     file_bytes = file.read()
+# image = Image.load_from_file(file_bytes)
+# if upload_image:
+#     image = Image.load_from_file(upload_image)
+
+generative_multimodal_model = GenerativeModel("gemini-1.0-pro-vision")
+response = generative_multimodal_model.generate_content(["Describe the image", image])
+# prompt="""Here are a few of the things that aren\'t allowed on this chat:
+# 1. Nudity or other sexually suggestive content
+# 2. Hate speech, credible threats or direct attacks on an individual or group
+# 3. Content that contains self-harm or excessive violence
+# 4. Fake or impostor profiles
+# 5. Spam
+
+# The following behaviour isn\'t allowed on this chat:
+# 1. Posting things that don\'t follow the Community Standards (e.g. threats, hate speech, graphic violence).
+# 2. Using Community to bully, impersonate or harass anyone.
+
+# User-1: Hold onto your hearts. \"Tiger 3\" will make you laugh, cry, and feel everything in between. In cinemas soon.
+# #love #heartbreak #feelgoodmovie
+# User-2: Loved your look in \"Tiger 3\"! You always look so hot and sexy.
+
+# User-1: Instead of politicians, let the monkeys govern the countries; at least they will steal only the bananas!
+# User-2: User-2\'s comment is not allowed on this chat because it contains sexually suggestive content.
+
+# User-1: Loved your look in \"Tiger 3\"! You always look so hot and sexy.
+# User-2: The response was blocked because the input or response may contain descriptions of violence, sexual themes, or otherwise derogatory content. Please try rephrasing your prompt.
+
+# User-1: Be courageous. Challenge orthodoxy. Stand up for what you believe in. When you are in your rocking chair talking to your grandchildren many years from now, be sure you have a good story to tell
+# User-2:
+# stricly follow prompt analyse {response.text} and declare output as "positive or negative" 
+# """
+prompt=""" Analyse the {response.text} and understand the content provided in {response.text} 
+whether the content is sarcastic postive or negative etc and
+ declare the output as "positive" or "negative"
+"""
+print(response.text)
+result=generative_multimodal_model.generate_content([prompt,response.text])
+print(result.text)
+
+# import http.client
+# import typing
+# import urllib.request
+# from vertexai.generative_models import GenerativeModel, Image
+
+# # create helper function
+# def load_image_from_url(image_url: str) -> Image:
+#     with urllib.request.urlopen(image_url) as response:
+#         response = typing.cast(http.client.HTTPResponse, response)
+#         image_bytes = response.read()
+#     return Image.from_bytes(image_bytes)
+
+# # Load images from Cloud Storage URI
+# landmark1 = load_image_from_url(
+#     "https://storage.googleapis.com/cloud-samples-data/vertex-ai/llm/prompts/landmark1.png"
+# )
+# landmark2 = load_image_from_url(
+#     "https://storage.googleapis.com/cloud-samples-data/vertex-ai/llm/prompts/landmark2.png"
+# )
+# landmark3 = load_image_from_url(
+#     "https://storage.googleapis.com/cloud-samples-data/vertex-ai/llm/prompts/landmark3.png"
+# )
+
+# # Pass multimodal prompt
+# model = GenerativeModel("gemini-1.0-pro-vision")
+# response = model.generate_content(
+#     [
+#         landmark1,
+#         "city: Rome, Landmark: the Colosseum",
+#         landmark2,
+#         "city: Beijing, Landmark: Forbidden City",
+#         landmark3,
+#     ]
+# )
+# print(response)