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# img_gen.py
import sys
import os
import random
from huggingface_hub import InferenceClient, login
from datetime import datetime
from config.config import models, prompts, api_token # Direct import
def generate_image(
prompt_alias,
team_color,
custom_prompt,
model_alias="FLUX.1-dev",
height=360,
width=640,
num_inference_steps=20,
guidance_scale=2.0,
seed=-1):
# Find the selected prompt and model
try:
prompt = next(p for p in prompts if p["alias"] == prompt_alias)["text"]
#model_name = next(m for m in models if m["alias"] == model_alias)["name"]
model_name = f"black-forest-labs/{model_alias}"
except StopIteration:
return None, "ERROR: Invalid prompt or model selected."
# Determine the enemy color
enemy_color = "blue" if team_color.lower() == "red" else "red"
# if team.lower() == "red":
# winning_team_text = " The winning army is dressed in red armor and banners."
# elif team.lower() == "blue":
# winning_team_text = " The winning army is dressed in blue armor and banners."
# Print the original prompt and dynamic values for debugging
print("Original Prompt:")
print(prompt)
print(f"Enemy Color: {enemy_color}")
print(f"Team Color: {team_color.lower()}")
prompt = prompt.format(team_color=team_color.lower(), enemy_color=enemy_color)
# Append the custom prompt (if provided)
if custom_prompt and len(custom_prompt.strip()) > 0:
prompt += " " + custom_prompt.strip()
# Print the formatted prompt for debugging
print("\nFormatted Prompt:")
print(prompt)
# Randomize the seed if needed
if seed == -1:
seed = random.randint(0, 1000000)
# HF LOGIN
print("Initializing HF TOKEN")
print (api_token)
# login(token=api_token)
# print("model_name:")
# print(model_name)
# Initialize the InferenceClient
try:
print("-----INITIALIZING INFERENCE-----")
client = InferenceClient(model_name, token=api_token)
print("Inference activated")
except Exception as e:
return None, f"ERROR: Failed to initialize InferenceClient. Details: {e}"
#Generate the image
try:
print("-----GENERATING IMAGE-----")
image = client.text_to_image(
prompt,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
width=width,
height=height,
seed=seed
)
print("-----IMAGE GENERATED SUCCESSFULLY!-----")
except Exception as e:
return None, f"ERROR: Failed to generate image. Details: {e}"
# Save the image with a timestamped filename
print("-----SAVING-----", image)
path = "images"
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
output_filename = f"{path}/{timestamp}_{model_alias.replace(' ', '_').lower()}_{prompt_alias.replace(' ', '_').lower()}_{team_color.lower()}.png"
try:
image.save(output_filename)
except Exception as e:
return None, f"ERROR: Failed to save image. Details: {e}"
print("-----DONE!-----")
return output_filename, "Image generated successfully!" |