import os, sys, json, re, base64, random, requests, shutil import gradio as gr from datetime import datetime import urllib.parse from groq import Groq from exif import Image from PIL import Image as PILImage import colorsys MAX_SEED = 9999 MAX_IMAGE_SIZE = 2048 GROQ_APIKEY_PROMPTENHANCE = os.environ["GROQ_APIKEY_PROMPTENHANCE"] # delete cache folder if exist and create new CACHE_DIR = os.path.join(os.path.dirname(__file__), "cache") IMAGE_DIR = os.path.join(CACHE_DIR, "images") if os.path.exists(CACHE_DIR): shutil.rmtree(CACHE_DIR) os.makedirs(CACHE_DIR) os.makedirs(IMAGE_DIR) RES = os.path.join(os.path.dirname(__file__), "_res") custom_css = RES + "/_custom.css" custom_js = RES + "/_custom.js" title = "Pollinations Image Generator" description = "Pollinations API + Randomizer" theme = gr.themes.Soft( primary_hue="amber", radius_size="sm", ) def read_exif(image_path): with open(image_path, "rb") as src: img = Image(src) img_comment = json.loads(img.user_comment) # checking if the key exists before removing if "concept" in img_comment: img_comment.pop("concept") return img_comment def read_image_exfi_data(image_path): print("Imagepath:", image_path) img_exif_make, img_exif_comment = read_exif(image_path) return None, image_path, img_exif_comment def groq_enhance_process(Prompt): client = Groq(api_key=GROQ_APIKEY_PROMPTENHANCE) SYSTEMPROMPT = os.path.join(RES, "groq_systemmessage_prompt_enhance.json") with open(SYSTEMPROMPT, "r") as f: SYSTEMPROMPT = json.load(f) completion = client.chat.completions.create( model="llama-3.1-70b-versatile", messages=[SYSTEMPROMPT, {"role": "user", "content": Prompt}], temperature=0.8, max_tokens=8000, top_p=0.9, stream=False, stop=None, ) if completion.choices[0].message.content != "": enhanced_prompt = completion.choices[0].message.content return enhanced_prompt def enhance_process(Prompt): encode_prompt = urllib.parse.quote(Prompt) request_url = f"https://image.pollinations.ai/prompt/{encode_prompt}?model=turbo&width=512&height=512&nologo=true&enhance=true&nofeed=true" print(request_url) response = requests.get(request_url) if response.status_code == 200: filename = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") + ".png" file_path = os.path.join(CACHE_DIR, filename) with open(file_path, "wb") as f: f.write(response.content) img_exif_comment = read_exif(file_path) prompt_value = img_exif_comment.get("prompt", "") prompt_value = prompt_value.replace(Prompt, "").strip() print(prompt_value) return prompt_value def image_get_colors(image_path): img = PILImage.open(image_path) img = img.convert("RGB") pixels = list(img.getdata()) # Erzeuge eine Liste mit den Häufigkeiten der Farben colors = [] for pixel in pixels: r, g, b = pixel h, s, v = colorsys.rgb_to_hsv(r / 255, g / 255, b / 255) if v > 0.5: # Filteriere hellere Farben aus continue if v > 0.99: # Filteriere Weiß aus continue colors.append((h, s, v)) # Ermittle die dominante Farbe dominant_color = max(colors, key=lambda x: x[2]) dominant_color_rgb = colorsys.hsv_to_rgb(dominant_color[0], dominant_color[1], dominant_color[2]) dominant_color_rgb = [int(c * 255) for c in dominant_color_rgb] print(dominant_color_rgb) return dominant_color_rgb def process(Prompt, image_width, image_height, image_seed, randomize_seed): used_seed = random.randint(0, MAX_SEED) if image_seed == 0 or randomize_seed else image_seed timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") filename = timestamp + ".png" # file_path = os.path.join(filename_dir, filename) file_path = os.path.join(IMAGE_DIR, filename) encode_prompt = urllib.parse.quote(Prompt) request_url = f"https://image.pollinations.ai/prompt/{encode_prompt}?model=flux&width={image_width}&height={image_height}&nologo=true&enhance=false&nofeed=true&seed={used_seed}" print(request_url) response = requests.get(request_url) if response.status_code == 200: with open(file_path, "wb") as f: f.write(response.content) img_exif_comment = read_exif(file_path) img_dominant_color = image_get_colors(file_path) return ({"value": file_path, "__type__": "update"}, {"value": request_url, "visible": True, "__type__": "update"}, used_seed, img_exif_comment, {"visible": True, "__type__": "update"}, {"value": Prompt, "visible": True, "__type__": "update"}, {"value": file_path, "visible": True, "__type__": "update"}) with gr.Blocks(theme=theme, css=custom_css) as demo: with gr.Tab("Image Generator"): with gr.Row(): with gr.Column(scale=1): with gr.Row(): text_prompt = gr.Textbox(label="Prompt", show_label=False, lines=12, max_lines=18, placeholder="Enter your Image prompt here...", elem_classes="prompt-input", autofocus=True) with gr.Row(): with gr.Column(scale=2, elem_classes="image_size_selctor_wrapper"): image_width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, value=1024, step=128, elem_classes="image-width-selector") image_height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, value=683, step=128, elem_classes="image-height-selector") # with gr.Row(): # image_ratio_buttons = gr.Radio(["16:9", "4:3", "3:2", "1:1"], value="3:2", label="Bild Größe", interactive=True, elem_classes="image-ratio-buttons", container=True, show_label=False) # switch_width_height = gr.Button("🔁", size="sm", elem_id="switchRatioBtn", elem_classes="switch-ratio-btn", variant="primary") with gr.Row(): with gr.Column(): image_seed = gr.Slider(label="Seed", minimum=0, step=1, value=42, maximum=MAX_SEED) randomize_seed = gr.Checkbox(label="Randomize seed", value=False) with gr.Row(): run_button = gr.Button("Erstellen", variant="primary", elem_classes="run_button") enhance_button = gr.Button("Prompt verbessern", variant="secondary", elem_classes="enhance-button") with gr.Column(scale=3): with gr.Row(): with gr.Column(scale=3): output_image = gr.Image(show_label=False, height=720) with gr.Column(scale=1): image_informations = gr.Markdown("""## Bildinformationen""", visible=False) # textbox_your_prompt = gr.Textbox(label="Dein Prmopt", lines=2, max_lines=4, interactive=False, show_copy_button=True) textbox_prompt = gr.Textbox("Bild Prompt", lines=4, max_lines=8, interactive=False, show_copy_button=True, visible=False) image_download_button = gr.DownloadButton("Bild herunterladen", value=None, elem_classes="download-button", variant="Primary", visible=False) # output_image = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery", columns=[1], rows=[1], object_fit="contain", height="768") output_url = gr.Textbox(label="Output URL", show_label=True, interactive=False, show_copy_button=True, visible=False) outpu_image_comment = gr.Json(visible=False) # output_image = gr.Image(label="Generated image", show_label=True, height=720, show_share_button=False) # gallery = gr.Gallery(label="Generated Gallery", show_label=True, elem_id="gallery", columns=[3], rows=[1], object_fit="contain", height="auto", type="filepath") # testimage = gr.Image(value="images/2024-08-22/2024-08-22_00-45-31.png", type="pil") # gr.HTML("
") # for image_path in os.listdir(images_dir): # gr.HTML(f'') # gr.HTML("
") def switch_image_size_values(image_width, image_height): return image_height, image_width switch_width_height.click(fn=switch_image_size_values, inputs=[image_width, image_height], outputs=[image_width, image_height]) run_button.click(fn=process, inputs=[text_prompt, image_width, image_height, image_seed, randomize_seed], outputs=[output_image, output_url, image_seed, outpu_image_comment, image_informations, textbox_prompt, image_download_button]) enhance_button.click(fn=groq_enhance_process, inputs=[text_prompt], outputs=[text_prompt]) demo.launch() """ ## Endpoint GET https://image.pollinations.ai/prompt/{prompt} ## Description This endpoint generates an image based on the provided prompt and optional parameters. It returns a raw image file. ## Parameters - prompt (required): The text description of the image you want to generate. Should be URL-encoded. - model (optional): The model to use for generation. Options: 'flux' or 'turbo'. Default: 'turbo' - seed (optional): Seed for reproducible results. Default: random - width (optional): Width of the generated image. Default: 1024 - height (optional): Height of the generated image. Default: 1024 - nologo (optional): Set to 'true' to turn off the rendering of the logo - nofeed (optional): Set to 'true' to prevent the image from appearing in the public feed - enhance (optional): Set to 'true' or 'false' to turn on or off prompt enhancing (passes prompts through an LLM to add detail) ## Example Usage https://image.pollinations.ai/prompt/A%20beautiful%20sunset%20over%20the%20ocean?model=flux&width=1280&height=720&seed=42&nologo=true&enhance=true ## Response The API returns a raw image file (typically JPEG or PNG) as the response body. """