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refactor: Move assets to correct categories (fence→environment, chest→items, campfire already in workstations)

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David Kotnik
2025-12-30 03:05:12 +01:00
parent 56fd205ac1
commit f5a80a12b9
24 changed files with 1099 additions and 315 deletions
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scripts/test_single_asset.py
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@@ -1,183 +1,152 @@
#!/usr/bin/env python3
"""
Test script - generates single asset to verify ComfyUI workflow
"""
import os
import json
import time
import requests
from pathlib import Path
import copy
import subprocess
COMFYUI_URL = "http://127.0.0.1:8000"
OUTPUT_DIR = "/Users/davidkotnik/repos/novafarma/assets/images"
# Test prompt with all requirements
TEST_PROMPT = "Top-down 2.5D video game sprite, 128x128 pixels, smooth vector art style like Stardew Valley, NO pixels, vibrant colors, clean edges, GREEN SCREEN background RGBA(0,255,0,255) pure green chroma key, Normal farm cow black and white Holstein pattern friendly face 4-direction sprite"
def queue_comfy_prompt(prompt_text: str, output_name: str) -> dict:
"""Send prompt to ComfyUI"""
workflow = {
"3": {
"inputs": {
"seed": int(time.time()),
"steps": 25,
"cfg": 7.5,
"sampler_name": "euler",
"scheduler": "normal",
"denoise": 1,
"model": ["4", 0],
"positive": ["6", 0],
"negative": ["7", 0],
"latent_image": ["5", 0]
},
"class_type": "KSampler"
workflow = {
"3": {
"inputs": {
"seed": int(time.time()),
"steps": 25,
"cfg": 7.5,
"sampler_name": "euler",
"scheduler": "normal",
"denoise": 1,
"model": ["4", 0],
"positive": ["6", 0],
"negative": ["7", 0],
"latent_image": ["5", 0]
},
"4": {
"inputs": {
"ckpt_name": "sd_xl_base_1.0.safetensors"
},
"class_type": "CheckpointLoaderSimple"
"class_type": "KSampler"
},
"4": {
"inputs": {
"ckpt_name": "v1-5-pruned-emaonly.safetensors"
},
"5": {
"inputs": {
"width": 128,
"height": 128,
"batch_size": 1
},
"class_type": "EmptyLatentImage"
"class_type": "CheckpointLoaderSimple"
},
"5": {
"inputs": {
"width": 512,
"height": 512,
"batch_size": 1
},
"6": {
"inputs": {
"text": prompt_text,
"clip": ["4", 1]
},
"class_type": "CLIPTextEncode"
"class_type": "EmptyLatentImage"
},
"6": {
"inputs": {
"text": "",
"clip": ["4", 1],
"class_type": "CLIPTextEncode"
},
"7": {
"inputs": {
"text": "blurry, low quality, pixelated, photo, realistic",
"clip": ["4", 1]
},
"7": {
"inputs": {
"text": "blurry, low quality, pixelated, voxel, 3D render, realistic photo",
"clip": ["4", 1]
},
"class_type": "CLIPTextEncode"
"class_type": "CLIPTextEncode"
},
"8": {
"inputs": {
"samples": ["3", 0],
"vae": ["4", 2]
},
"8": {
"inputs": {
"samples": ["3", 0],
"vae": ["4", 2]
},
"class_type": "VAEDecode"
"class_type": "VAEDecode"
},
"9": {
"inputs": {
"filename_prefix": "",
"images": ["8", 0],
},
"9": {
"inputs": {
"filename_prefix": output_name,
"images": ["8", 0]
},
"class_type": "SaveImage"
}
"class_type": "SaveImage"
}
}
def queue_prompt(prompt):
p = {"prompt": prompt}
data = json.dumps(p).encode('utf-8')
try:
response = requests.post(
f"{COMFYUI_URL}/prompt",
json={"prompt": workflow}
)
return response.json()
res = requests.post(COMFYUI_URL + "/prompt", data=data)
if res.status_code == 200:
print("🚀 SUCCESS: Poslano v ComfyUI!")
return res.json()
else:
print(f"❌ Napaka: {res.text}")
return None
except Exception as e:
print(f"❌ Error: {e}")
print(f"❌ UFI (ComfyUI) ni prižgan! {e}")
return None
def wait_for_completion(prompt_id: str, timeout: int = 180) -> bool:
"""Wait for generation"""
start = time.time()
while time.time() - start < timeout:
try:
response = requests.get(f"{COMFYUI_URL}/history/{prompt_id}")
history = response.json()
r = requests.get(f"{COMFYUI_URL}/history/{prompt_id}")
history = r.json()
if prompt_id in history:
status = history[prompt_id].get("status", {})
if status.get("completed", False):
status = history[prompt_id].get('status', {})
if status.get('completed'):
return True
except Exception as e:
print(f"⚠️ Polling: {e}")
except Exception:
pass
time.sleep(2)
return False
def download_image(prompt_id: str, output_path: Path) -> bool:
"""Download image"""
def download_image(prompt_id: str, prefix: str):
try:
response = requests.get(f"{COMFYUI_URL}/history/{prompt_id}")
history = response.json()
r = requests.get(f"{COMFYUI_URL}/history/{prompt_id}")
history = r.json()
if prompt_id not in history:
return False
outputs = history[prompt_id].get("outputs", {})
for node_id, node_output in outputs.items():
if "images" in node_output:
for img in node_output["images"]:
filename = img["filename"]
subfolder = img.get("subfolder", "")
img_url = f"{COMFYUI_URL}/view"
params = {
"filename": filename,
"subfolder": subfolder,
"type": "output"
}
img_response = requests.get(img_url, params=params)
if img_response.status_code == 200:
output_path.parent.mkdir(parents=True, exist_ok=True)
with open(output_path, 'wb') as f:
f.write(img_response.content)
outputs = history[prompt_id].get('outputs', {})
for node_id, out in outputs.items():
if 'images' in out:
for img in out['images']:
filename = img['filename']
subfolder = img.get('subfolder', '')
url = f"{COMFYUI_URL}/view"
params = {'filename': filename, 'subfolder': subfolder, 'type': 'output'}
img_resp = requests.get(url, params=params)
if img_resp.status_code == 200:
out_path = os.path.join(OUTPUT_DIR, f"{prefix}_{filename}")
os.makedirs(os.path.dirname(out_path), exist_ok=True)
with open(out_path, 'wb') as f:
f.write(img_resp.content)
print(f"✅ Image saved: {out_path}")
# subprocess.run(["open", out_path])
return True
return False
except Exception as e:
print(f"❌ Download error: {e}")
return False
print("=" * 70)
print("🧪 TEST: Single Asset Generation")
print("=" * 70)
print(f"📡 Server: {COMFYUI_URL}")
print(f"🎨 Prompt: {TEST_PROMPT[:80]}...")
print()
# Updated generate_character to use new helpers
# Check connection
try:
response = requests.get(f"{COMFYUI_URL}/system_stats")
print("✅ ComfyUI connected!")
except:
print("❌ ComfyUI NOT responding!")
exit(1)
# Queue test
print("\n🚀 Queuing test generation...")
result = queue_comfy_prompt(TEST_PROMPT, "test_cow")
if not result or "prompt_id" not in result:
print("❌ Failed to queue!")
exit(1)
prompt_id = result["prompt_id"]
print(f"⏳ Queued: {prompt_id}")
# Wait
print("⏳ Waiting for completion...")
if wait_for_completion(prompt_id):
output_path = Path(OUTPUT_DIR) / "zivali" / "test_cow.png"
if download_image(prompt_id, output_path):
print(f"✅ SUCCESS! Saved to: {output_path}")
print("\n📊 Check the image:")
print(f" - Size should be 128x128")
print(f" - Background should be green RGBA(0,255,0,255)")
print(f" - Style should be smooth 2D vector art")
def generate_character(name, prompt_text, prefix):
wf = copy.deepcopy(workflow)
wf["6"]["inputs"]["text"] = prompt_text
wf["9"]["inputs"]["filename_prefix"] = prefix
result = queue_prompt(wf)
if not result or 'prompt_id' not in result:
print('❌ Failed to get prompt_id')
return
pid = result['prompt_id']
if wait_for_completion(pid):
download_image(pid, prefix)
else:
print("❌ Failed to download!")
else:
print("⏱️ Timeout!")
print('❌ Generation timed out')
# Generate 5 Kai images
kai_prompt = "Top-down 2.5D, (bold black outlines:1.4), dark hand-drawn stylized indie game art, high contrast noir style, character Kai with pink and green dreadlocks, friendly smile"
for i in range(5):
generate_character("Kai", kai_prompt, f"noir_kai_{i}")
# Generate 5 Gronk images
gronk_prompt = "Top-down 2.5D, (bold black outlines:1.4), dark hand-drawn stylized indie game art, high contrast noir style, character Gronk with pink dreadlocks, stretched ears, facial piercings, holding a vape"
for i in range(5):
generate_character("Gronk", gronk_prompt, f"noir_gronk_{i}")