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873ac58 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 | import streamlit as st
import json
import time
from PIL import Image
import os
import sys
import shutil
import gdown
from io import BytesIO
# ==================================
# SETUP
# ==================================
print("🚀 Streamlit App Starting...")
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
# Setup Paths
UPLOAD_DIR = "/tmp/uploads/"
MODEL_DIR = os.path.join(BASE_DIR, "rcnn_model", "scripts")
JSON_DIR = "/tmp/results/"
OUTPUT_DIR = "/tmp/output/"
SAMPLE_DIR = os.path.join(BASE_DIR, "rcnn_model", "sample")
logo_path = os.path.join(BASE_DIR, "public", "logo.png")
model_path = os.path.join(OUTPUT_DIR, "model_final.pth")
# Google Drive file download link
GOOGLE_DRIVE_FILE_ID = "1yr64AOgaYZPTcQzG6cxG6lWBENHR9qjW"
GDRIVE_URL = f"https://drive.google.com/uc?id={GOOGLE_DRIVE_FILE_ID}"
# Create necessary folders
os.makedirs(UPLOAD_DIR, exist_ok=True)
os.makedirs(JSON_DIR, exist_ok=True)
os.makedirs(OUTPUT_DIR, exist_ok=True)
# ==================================
# DOWNLOAD MODEL IF MISSING
# ==================================
if not os.path.exists(model_path):
print("🚀 Model file not found! Downloading from Google Drive...")
try:
gdown.download(GDRIVE_URL, model_path, quiet=False)
print("✅ Model downloaded successfully.")
except Exception as e:
print(f"❌ Failed to download model: {e}")
# ==================================
# IMPORT MODEL RUNNER
# ==================================
sys.path.append(MODEL_DIR)
from rcnn_model.scripts.rcnn_run import main, write_config
# ==================================
# PAGE CONFIG
# ==================================
st.set_page_config(
page_title="2D Floorplan Vectorizer",
layout="wide",
initial_sidebar_state="collapsed"
)
# ==================================
# HEADER
# ==================================
st.image(logo_path, width=250)
st.markdown("<div class='header-title'>2D Floorplan Vectorizer</div>", unsafe_allow_html=True)
# ==================================
# FILE UPLOAD SECTION
# ==================================
st.subheader("Upload your Floorplan Image")
uploaded_file = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
# Initialize session state
if "processing_complete" not in st.session_state:
st.session_state.processing_complete = False
if "json_output" not in st.session_state:
st.session_state.json_output = None
# ==================================
# IMAGE + JSON Layout
# ==================================
col1, col2 = st.columns([1, 2])
# ==================================
# MAIN LOGIC
# ==================================
if uploaded_file is not None:
print("📤 File Uploaded:", uploaded_file.name)
image_bytes = uploaded_file.read()
img = Image.open(BytesIO(image_bytes)).convert("RGB")
uploaded_path = os.path.join(UPLOAD_DIR, uploaded_file.name)
with open(uploaded_path, "wb") as f:
f.write(uploaded_file.getbuffer())
print("✅ Uploaded file saved at:", uploaded_path)
with col1:
st.markdown("<div class='upload-container'>", unsafe_allow_html=True)
st.image(Image.open(uploaded_path), caption="Uploaded Image", use_container_width=True)
st.markdown("</div>", unsafe_allow_html=True)
with col2:
if not st.session_state.processing_complete:
status_placeholder = st.empty()
status_placeholder.info("⏳ Model is processing the uploaded image...")
progress_bar = st.progress(0)
status_text = st.empty()
# === 🔥 Model Run Here ===
input_image = uploaded_path
output_json_name = uploaded_file.name.replace(".png", "_result.json").replace(".jpg", "_result.json").replace(".jpeg", "_result.json")
output_image_name = uploaded_file.name.replace(".png", "_result.png").replace(".jpg", "_result.png").replace(".jpeg", "_result.png")
output_json_path = os.path.join(JSON_DIR, output_json_name)
output_image_path = os.path.join(JSON_DIR, output_image_name)
cfg = write_config()
print("⚙️ Model config created. Running model...")
# Simulate progress
for i in range(1, 30):
time.sleep(0.01)
progress_bar.progress(i)
status_text.text(f"Preprocessing: {i}%")
# Run model
main(cfg, input_image, output_json_path, output_image_path)
print("✅ Model run complete.")
while not os.path.exists(output_json_path):
print("Waiting for JSON output...")
time.sleep(0.5)
for i in range(30, 100):
time.sleep(0.01)
progress_bar.progress(i)
status_text.text(f"Postprocessing: {i}%")
progress_bar.empty()
status_text.text("✅ Processing Complete!")
status_placeholder.success("✅ Model finished and JSON is ready!")
# Read generated JSON
if os.path.exists(output_json_path):
with open(output_json_path, "r") as jf:
st.session_state.json_output = json.load(jf)
print("📄 JSON Output Loaded Successfully.")
else:
st.session_state.json_output = {"error": "JSON output not generated."}
print("❌ JSON output missing.")
st.session_state.processing_complete = True
# ==================================
# DISPLAY OUTPUTS
# ==================================
out_col1, out_col2 = st.columns(2)
with out_col1:
if os.path.exists(output_image_path):
with open(output_image_path, "rb") as img_file:
image = Image.open(img_file)
st.image(image, caption="🖼 Output Vectorized Image", use_container_width=True)
img_file.seek(0)
st.download_button(
label="Download Output Image",
data=img_file,
file_name="floorplan_output.png",
mime="image/png"
)
if os.path.exists(output_json_path):
json_str = json.dumps(st.session_state.json_output, indent=4)
st.download_button(
label="Download JSON",
data=json_str,
file_name="floorplan_output.json",
mime="application/json"
)
with out_col2:
st.markdown("<div class='json-container'>", unsafe_allow_html=True)
st.json(st.session_state.json_output)
st.markdown("</div>", unsafe_allow_html=True)
else:
st.warning("⚠️ No image uploaded yet.")
st.session_state.processing_complete = False
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