notebookVb

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administrator
2026-05-24 07:45:59 +02:00
parent ff293b28ca
commit 662c890257
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import sys, io
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
import psycopg2
conn = psycopg2.connect(host='192.168.1.76', port=5432, dbname='fotky_buzalkovi',
user='vladimir.buzalka', password='Vlado7309208104++')
cur = conn.cursor()
# 1. Duplikáty sha256_pixels
print('=== DUPLIKÁTY sha256_pixels ===')
cur.execute('''SELECT sha256_pixels, COUNT(*) as cnt FROM photos
WHERE sha256_pixels IS NOT NULL GROUP BY sha256_pixels HAVING COUNT(*) > 1
ORDER BY cnt DESC LIMIT 10''')
for r in cur.fetchall():
print(f' {r[0][:16]}... : {r[1]}x')
cur.execute('''SELECT COUNT(*), SUM(cnt) FROM (
SELECT COUNT(*) as cnt FROM photos WHERE sha256_pixels IS NOT NULL
GROUP BY sha256_pixels HAVING COUNT(*) > 1) x''')
r = cur.fetchone()
print(f'Celkem skupin duplikátů: {r[0]}, fotek v duplikátech: {r[1]}')
# 2. Identické phash
print('\n=== IDENTICKÉ phash ===')
cur.execute('''SELECT phash, COUNT(*) as cnt FROM photos
WHERE phash IS NOT NULL GROUP BY phash HAVING COUNT(*) > 1
ORDER BY cnt DESC LIMIT 10''')
for r in cur.fetchall():
print(f' phash={r[0]}: {r[1]}x')
cur.execute('''SELECT COUNT(*), SUM(cnt) FROM (
SELECT COUNT(*) as cnt FROM photos WHERE phash IS NOT NULL
GROUP BY phash HAVING COUNT(*) > 1) x''')
r = cur.fetchone()
print(f'Celkem skupin: {r[0]}, fotek: {r[1]}')
# 3. Screenshoty
print('\n=== SCREENSHOTY ===')
cur.execute('SELECT COUNT(*) FROM photos WHERE is_screenshot = true')
print(f'is_screenshot=true: {cur.fetchone()[0]}')
# 4. Objektivy
print('\n=== TOP OBJEKTIVY ===')
cur.execute('''SELECT COALESCE(lens_model, '(neuvedeno)') as lens, COUNT(*) as cnt
FROM photos GROUP BY lens ORDER BY cnt DESC LIMIT 15''')
for r in cur.fetchall():
print(f' {r[1]:>6} {r[0]}')
# 5. ISO distribuce
print('\n=== ISO DISTRIBUCE ===')
cur.execute('''SELECT iso, COUNT(*) as cnt FROM photos WHERE iso IS NOT NULL
GROUP BY iso ORDER BY cnt DESC LIMIT 15''')
for r in cur.fetchall():
print(f' ISO {r[0]:>6}: {r[1]}')
# 6. Clona
print('\n=== CLONA (aperture) TOP ===')
cur.execute('''SELECT aperture, COUNT(*) as cnt FROM photos WHERE aperture IS NOT NULL
GROUP BY aperture ORDER BY cnt DESC LIMIT 15''')
for r in cur.fetchall():
print(f' f/{r[0]}: {r[1]}')
# 7. Expoziční čas
print('\n=== EXPOZIČNÍ ČAS TOP ===')
cur.execute('''SELECT exposure_time, COUNT(*) as cnt FROM photos WHERE exposure_time IS NOT NULL
GROUP BY exposure_time ORDER BY cnt DESC LIMIT 15''')
for r in cur.fetchall():
print(f' {r[0]}: {r[1]}')
# 8. GPS top lokace
print('\n=== GPS TOP LOKACE (zaokrouhleno na 0.1 stupne) ===')
cur.execute('''SELECT ROUND(gps_lat::numeric, 1) as lat, ROUND(gps_lon::numeric, 1) as lon, COUNT(*) as cnt
FROM photos WHERE gps_lat IS NOT NULL AND gps_lon IS NOT NULL
GROUP BY lat, lon ORDER BY cnt DESC LIMIT 20''')
for r in cur.fetchall():
print(f' [{r[0]}, {r[1]}]: {r[2]} fotek')
cur.execute('''SELECT MIN(gps_lat), MAX(gps_lat), MIN(gps_lon), MAX(gps_lon)
FROM photos WHERE gps_lat IS NOT NULL''')
r = cur.fetchone()
print(f' Rozsah Lat: {r[0]} .. {r[1]}')
print(f' Rozsah Lon: {r[2]} .. {r[3]}')
# 9. Megapixely po letech
print('\n=== PRUMERNE MEGAPIXELY PO LETECH ===')
cur.execute('''SELECT EXTRACT(YEAR FROM taken_at)::INT as rok,
ROUND(AVG(megapixels)::numeric, 1) as avg_mp,
ROUND(MAX(megapixels)::numeric, 1) as max_mp, COUNT(*) as cnt
FROM photos WHERE taken_at IS NOT NULL AND megapixels IS NOT NULL
GROUP BY rok ORDER BY rok''')
for r in cur.fetchall():
print(f' {r[0]}: avg={r[1]} MP, max={r[2]} MP ({r[3]} fotek)')
# 10. Formáty
print('\n=== FORMATY ===')
cur.execute('''SELECT COALESCE(file_ext, '(none)') as ext, COUNT(*) as cnt
FROM photos GROUP BY ext ORDER BY cnt DESC''')
for r in cur.fetchall():
print(f' {r[0]}: {r[1]}')
# 11. Průhlednost
print('\n=== PRUHLEDNOST ===')
cur.execute('SELECT COUNT(*) FROM photos WHERE has_transparency = true')
print(f' S pruhlednosti: {cur.fetchone()[0]}')
# 12. Barevné módy
print('\n=== BAREVNE MODY ===')
cur.execute('''SELECT COALESCE(mode, '(none)') as m, COUNT(*) as cnt
FROM photos GROUP BY m ORDER BY cnt DESC''')
for r in cur.fetchall():
print(f' {r[0]}: {r[1]}')
# 13. Neznámé fotky - vzory názvů
print('\n=== NEZNAME FOTKY 2015-2016 (bez kamery) - vzory nazvu ===')
cur.execute('''SELECT file_name FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) BETWEEN 2015 AND 2016
LIMIT 30''')
for r in cur.fetchall():
print(f' {r[0]}')
print('\n=== NEZNAME FOTKY 2022 - vzory nazvu ===')
cur.execute('''SELECT file_name FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) = 2022
LIMIT 30''')
for r in cur.fetchall():
print(f' {r[0]}')
print('\n=== 2022 PREFIXES ===')
cur.execute('''SELECT LEFT(file_name, 10) as prefix, COUNT(*) as cnt FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) = 2022
GROUP BY prefix ORDER BY cnt DESC LIMIT 15''')
for r in cur.fetchall():
print(f' {r[0]}: {r[1]}')
# 14. Měsíce
print('\n=== FOTKY PO MESICICH ===')
nazvy = ['','Leden','Unor','Brezen','Duben','Kveten','Cerven','Cervenec','Srpen','Zari','Rijen','Listopad','Prosinec']
cur.execute('''SELECT EXTRACT(MONTH FROM taken_at)::INT as mesic, COUNT(*) as cnt
FROM photos WHERE taken_at IS NOT NULL GROUP BY mesic ORDER BY mesic''')
for r in cur.fetchall():
print(f' {nazvy[r[0]]}: {r[1]}')
# 15. Dny v týdnu
print('\n=== FOTKY PO DNECH V TYDNU ===')
dny = ['Nedele','Pondeli','Utery','Streda','Ctvrtek','Patek','Sobota']
cur.execute('''SELECT EXTRACT(DOW FROM taken_at)::INT as den, COUNT(*) as cnt
FROM photos WHERE taken_at IS NOT NULL GROUP BY den ORDER BY den''')
for r in cur.fetchall():
print(f' {dny[r[0]]}: {r[1]}')
# 16. Hodiny
print('\n=== FOTKY PO HODINACH ===')
cur.execute('''SELECT EXTRACT(HOUR FROM taken_at)::INT as hod, COUNT(*) as cnt
FROM photos WHERE taken_at IS NOT NULL GROUP BY hod ORDER BY hod''')
for r in cur.fetchall():
print(f' {r[0]:02d}:00 - {r[1]}')
# 17. Top dny (události)
print('\n=== TOP 20 DNU (nejvic fotek = udalosti) ===')
cur.execute('''SELECT taken_at::date as den, COUNT(*) as cnt
FROM photos WHERE taken_at IS NOT NULL GROUP BY den ORDER BY cnt DESC LIMIT 20''')
for r in cur.fetchall():
print(f' {r[0]}: {r[1]} fotek')
conn.close()
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import streamlit as st
import psycopg2
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
st.set_page_config(page_title="FotkyBuzalkovi - Report", layout="wide", page_icon="📷")
@st.cache_resource
def get_conn():
return psycopg2.connect(
host="192.168.1.76", port=5432, dbname="fotky_buzalkovi",
user="vladimir.buzalka", password="Vlado7309208104++"
)
def q(sql, params=None):
conn = get_conn()
return pd.read_sql(sql, conn, params=params)
st.title("📷 FotkyBuzalkovi — Průzkum dat")
# --- Celkové statistiky ---
st.header("Celkové statistiky")
c1, c2, c3, c4 = st.columns(4)
counts = q("""
SELECT
(SELECT COUNT(*) FROM photos) as photos,
(SELECT COUNT(*) FROM photos WHERE exif_raw IS NOT NULL AND exif_raw != '{}') as s_exif,
(SELECT COUNT(*) FROM photos WHERE gps_lat IS NOT NULL) as s_gps,
(SELECT COUNT(*) FROM photos WHERE camera_model IS NOT NULL) as s_camera
""").iloc[0]
c1.metric("Celkem fotek", f"{counts['photos']:,}")
c2.metric("S EXIF daty", f"{counts['s_exif']:,}")
c3.metric("S GPS", f"{counts['s_gps']:,}")
c4.metric("S kamerou", f"{counts['s_camera']:,}")
# --- Zálohovací pipeline ---
st.subheader("Zálohovací pipeline (sběr fotek)")
z1, z2, z3 = st.columns(3)
zcounts = q("""
SELECT
(SELECT COUNT(*) FROM zaloha_obrazku) as zalohy,
(SELECT COUNT(*) FROM zdrojove_soubory) as zdroje,
(SELECT COUNT(*) FROM zdrojove_soubory) - (SELECT COUNT(*) FROM zaloha_obrazku) as duplikaty
""").iloc[0]
z1.metric("Unikátních záloh", f"{zcounts['zalohy']:,}")
z2.metric("Zdrojových souborů", f"{zcounts['zdroje']:,}")
z3.metric("Duplikátních výskytů", f"{zcounts['duplikaty']:,}")
st.divider()
# --- Fotky po letech ---
st.header("📅 Fotky po letech")
df_years = q("""
SELECT EXTRACT(YEAR FROM taken_at)::INT as rok, COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL
GROUP BY rok ORDER BY rok
""")
fig = px.bar(df_years, x="rok", y="pocet", text="pocet",
labels={"rok": "Rok", "pocet": "Počet fotek"})
fig.update_traces(textposition="outside", texttemplate="%{text:,}")
fig.update_layout(height=450)
st.plotly_chart(fig, use_container_width=True)
# --- Fotoaparáty po letech ---
st.header("📸 Fotoaparáty po letech")
df_cam = q("""
SELECT EXTRACT(YEAR FROM taken_at)::INT as rok,
COALESCE(camera_model, '(neznámý)') as model,
COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL
GROUP BY rok, model ORDER BY rok, pocet DESC
""")
selected_year = st.selectbox("Vyber rok:", sorted(df_cam["rok"].unique()), index=len(df_cam["rok"].unique())-5)
df_year_cam = df_cam[df_cam["rok"] == selected_year].head(15)
fig_cam = px.bar(df_year_cam, x="model", y="pocet", text="pocet",
labels={"model": "Fotoaparát", "pocet": "Počet fotek"},
title=f"Fotoaparáty v roce {selected_year}")
fig_cam.update_traces(textposition="outside")
fig_cam.update_layout(xaxis_tickangle=-45, height=500)
st.plotly_chart(fig_cam, use_container_width=True)
# Heatmapa kamery × rok (top 15 kamer celkově)
st.subheader("Heatmapa: top kamery × roky")
top_cameras = q("""
SELECT camera_model, COUNT(*) as cnt FROM photos
WHERE camera_model IS NOT NULL
GROUP BY camera_model ORDER BY cnt DESC LIMIT 15
""")["camera_model"].tolist()
df_heat = df_cam[df_cam["model"].isin(top_cameras)].pivot_table(
index="model", columns="rok", values="pocet", fill_value=0
)
fig_heat = px.imshow(df_heat, labels=dict(x="Rok", y="Fotoaparát", color="Fotek"),
aspect="auto", color_continuous_scale="YlOrRd")
fig_heat.update_layout(height=500)
st.plotly_chart(fig_heat, use_container_width=True)
st.divider()
# --- Duplikáty ---
st.header("🔄 Duplikáty")
d1, d2 = st.columns(2)
with d1:
st.subheader("Identické pixely (sha256_pixels)")
df_dup_px = q("""
SELECT COUNT(*) as skupin, SUM(cnt) as fotek FROM (
SELECT COUNT(*) as cnt FROM photos WHERE sha256_pixels IS NOT NULL
GROUP BY sha256_pixels HAVING COUNT(*) > 1
) x
""").iloc[0]
st.metric("Skupin duplikátů", f"{df_dup_px['skupin']:,}")
st.metric("Fotek v duplikátech", f"{df_dup_px['fotek']:,}")
with d2:
st.subheader("Vizuálně podobné (phash)")
df_dup_ph = q("""
SELECT COUNT(*) as skupin, SUM(cnt) as fotek FROM (
SELECT COUNT(*) as cnt FROM photos WHERE phash IS NOT NULL
GROUP BY phash HAVING COUNT(*) > 1
) x
""").iloc[0]
st.metric("Skupin podobných", f"{df_dup_ph['skupin']:,}")
st.metric("Fotek v podobných skupinách", f"{df_dup_ph['fotek']:,}")
st.divider()
# --- GPS mapa ---
st.header("🗺️ GPS lokace")
df_gps = q("""
SELECT gps_lat as lat, gps_lon as lon
FROM photos WHERE gps_lat IS NOT NULL AND gps_lon IS NOT NULL
""")
if not df_gps.empty:
df_gps["lat"] = df_gps["lat"].astype(float)
df_gps["lon"] = df_gps["lon"].astype(float)
st.map(df_gps, size=2)
st.subheader("Top lokace (zaokrouhleno na 0.1°)")
df_gps_top = q("""
SELECT ROUND(gps_lat::numeric, 1) as lat, ROUND(gps_lon::numeric, 1) as lon,
COUNT(*) as pocet
FROM photos WHERE gps_lat IS NOT NULL AND gps_lon IS NOT NULL
GROUP BY lat, lon ORDER BY pocet DESC LIMIT 20
""")
st.dataframe(df_gps_top, use_container_width=True)
st.divider()
# --- Technické parametry ---
st.header("⚙️ Technické parametry")
tab_iso, tab_clona, tab_exp, tab_lens = st.tabs(["ISO", "Clona", "Expoziční čas", "Objektivy"])
with tab_iso:
df_iso = q("""
SELECT iso, COUNT(*) as pocet FROM photos WHERE iso IS NOT NULL
GROUP BY iso ORDER BY pocet DESC LIMIT 20
""")
fig_iso = px.bar(df_iso, x="iso", y="pocet", text="pocet",
labels={"iso": "ISO", "pocet": "Počet fotek"})
fig_iso.update_traces(textposition="outside")
st.plotly_chart(fig_iso, use_container_width=True)
with tab_clona:
df_ap = q("""
SELECT aperture, COUNT(*) as pocet FROM photos WHERE aperture IS NOT NULL
GROUP BY aperture ORDER BY pocet DESC LIMIT 20
""")
df_ap["label"] = "f/" + df_ap["aperture"].astype(str)
fig_ap = px.bar(df_ap, x="label", y="pocet", text="pocet",
labels={"label": "Clona", "pocet": "Počet fotek"})
fig_ap.update_traces(textposition="outside")
st.plotly_chart(fig_ap, use_container_width=True)
with tab_exp:
df_exp = q("""
SELECT exposure_time, COUNT(*) as pocet FROM photos WHERE exposure_time IS NOT NULL
GROUP BY exposure_time ORDER BY pocet DESC LIMIT 20
""")
fig_exp = px.bar(df_exp, x="exposure_time", y="pocet", text="pocet",
labels={"exposure_time": "Expoziční čas", "pocet": "Počet fotek"})
fig_exp.update_traces(textposition="outside")
fig_exp.update_layout(xaxis_tickangle=-45)
st.plotly_chart(fig_exp, use_container_width=True)
with tab_lens:
df_lens = q("""
SELECT COALESCE(lens_model, '(neuvedeno)') as objektiv, COUNT(*) as pocet
FROM photos GROUP BY objektiv ORDER BY pocet DESC LIMIT 15
""")
st.dataframe(df_lens, use_container_width=True)
st.divider()
# --- Rozlišení po letech ---
st.header("📐 Megapixely po letech")
df_mp = q("""
SELECT EXTRACT(YEAR FROM taken_at)::INT as rok,
ROUND(AVG(megapixels)::numeric, 1) as prumer,
ROUND(MAX(megapixels)::numeric, 1) as maximum
FROM photos WHERE taken_at IS NOT NULL AND megapixels IS NOT NULL
GROUP BY rok ORDER BY rok
""")
fig_mp = go.Figure()
fig_mp.add_trace(go.Scatter(x=df_mp["rok"], y=df_mp["prumer"], mode="lines+markers", name="Průměr MP"))
fig_mp.add_trace(go.Scatter(x=df_mp["rok"], y=df_mp["maximum"], mode="lines+markers", name="Maximum MP"))
fig_mp.update_layout(yaxis_title="Megapixely", xaxis_title="Rok", height=400)
st.plotly_chart(fig_mp, use_container_width=True)
st.divider()
# --- Formáty a barevné módy ---
st.header("🎨 Formáty a barvy")
f1, f2 = st.columns(2)
with f1:
st.subheader("Přípony")
df_ext = q("""
SELECT COALESCE(file_ext, '(none)') as pripona, COUNT(*) as pocet
FROM photos GROUP BY pripona ORDER BY pocet DESC
""")
st.dataframe(df_ext, use_container_width=True)
with f2:
st.subheader("Barevné módy")
df_mode = q("""
SELECT COALESCE(mode, '(none)') as mod, COUNT(*) as pocet
FROM photos GROUP BY mod ORDER BY pocet DESC
""")
fig_mode = px.pie(df_mode, values="pocet", names="mod")
st.plotly_chart(fig_mode, use_container_width=True)
st.divider()
# --- Neznámé fotky ---
st.header("❓ Fotky bez kamery — analýza názvů")
tab_2015, tab_2022 = st.tabs(["20152016", "2022"])
with tab_2015:
df_unk15 = q("""
SELECT file_name, file_size, taken_at, taken_at_source
FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) BETWEEN 2015 AND 2016
ORDER BY taken_at LIMIT 50
""")
st.dataframe(df_unk15, use_container_width=True)
st.info("Přejmenované importním skriptem — vzor: `[NO MODEL] [MD5...]`")
with tab_2022:
df_unk22 = q("""
SELECT file_name, file_size, taken_at, taken_at_source
FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) = 2022
ORDER BY taken_at LIMIT 50
""")
st.dataframe(df_unk22, use_container_width=True)
df_prefix = q("""
SELECT LEFT(file_name, 10) as prefix, COUNT(*) as pocet FROM photos
WHERE camera_model IS NULL AND EXTRACT(YEAR FROM taken_at) = 2022
GROUP BY prefix ORDER BY pocet DESC LIMIT 10
""")
st.subheader("Prefixes")
st.dataframe(df_prefix, use_container_width=True)
st.info("4 194 z 4 210 importováno najednou 25.9.2023 — pravděpodobně hromadný export z iCloudu/Google Photos")
st.divider()
# --- Časové vzory ---
st.header("⏰ Časové vzory")
tab_month, tab_dow, tab_hour, tab_topdays = st.tabs(["Měsíce", "Dny v týdnu", "Hodiny", "Top dny (události)"])
with tab_month:
df_month = q("""
SELECT EXTRACT(MONTH FROM taken_at)::INT as mesic, COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL GROUP BY mesic ORDER BY mesic
""")
nazvy = {1:'Leden',2:'Únor',3:'Březen',4:'Duben',5:'Květen',6:'Červen',
7:'Červenec',8:'Srpen',9:'Září',10:'Říjen',11:'Listopad',12:'Prosinec'}
df_month["nazev"] = df_month["mesic"].map(nazvy)
fig_m = px.bar(df_month, x="nazev", y="pocet", text="pocet",
labels={"nazev": "Měsíc", "pocet": "Počet fotek"})
fig_m.update_traces(textposition="outside")
st.plotly_chart(fig_m, use_container_width=True)
with tab_dow:
df_dow = q("""
SELECT EXTRACT(DOW FROM taken_at)::INT as den, COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL GROUP BY den ORDER BY den
""")
dny = {0:'Neděle',1:'Pondělí',2:'Úterý',3:'Středa',4:'Čtvrtek',5:'Pátek',6:'Sobota'}
df_dow["nazev"] = df_dow["den"].map(dny)
fig_d = px.bar(df_dow, x="nazev", y="pocet", text="pocet",
labels={"nazev": "Den", "pocet": "Počet fotek"})
fig_d.update_traces(textposition="outside")
st.plotly_chart(fig_d, use_container_width=True)
with tab_hour:
df_hour = q("""
SELECT EXTRACT(HOUR FROM taken_at)::INT as hodina, COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL GROUP BY hodina ORDER BY hodina
""")
fig_h = px.bar(df_hour, x="hodina", y="pocet", text="pocet",
labels={"hodina": "Hodina", "pocet": "Počet fotek"})
fig_h.update_traces(textposition="outside", texttemplate="%{text:,}")
fig_h.update_layout(xaxis=dict(dtick=1))
st.plotly_chart(fig_h, use_container_width=True)
with tab_topdays:
df_topdays = q("""
SELECT taken_at::date as den, COUNT(*) as pocet
FROM photos WHERE taken_at IS NOT NULL
GROUP BY den ORDER BY pocet DESC LIMIT 30
""")
fig_td = px.bar(df_topdays, x="den", y="pocet", text="pocet",
labels={"den": "Datum", "pocet": "Počet fotek"})
fig_td.update_traces(textposition="outside")
fig_td.update_layout(xaxis_tickangle=-45, height=500)
st.plotly_chart(fig_td, use_container_width=True)
st.divider()
# --- EXIF pokrytí ---
st.header("📊 EXIF pokrytí")
df_coverage = q("""
SELECT
COUNT(*) FILTER (WHERE exif_raw IS NOT NULL AND exif_raw != '{}') as s_exif,
COUNT(*) FILTER (WHERE taken_at IS NOT NULL) as s_taken_at,
COUNT(*) FILTER (WHERE camera_model IS NOT NULL) as s_camera,
COUNT(*) FILTER (WHERE iso IS NOT NULL) as s_iso,
COUNT(*) FILTER (WHERE gps_lat IS NOT NULL) as s_gps,
COUNT(*) FILTER (WHERE aperture IS NOT NULL) as s_aperture,
COUNT(*) FILTER (WHERE lens_model IS NOT NULL) as s_lens,
COUNT(*) as celkem
FROM photos
""").iloc[0]
categories = ["EXIF data", "Datum pořízení", "Model kamery", "ISO", "Clona", "GPS", "Objektiv"]
values = [
int(df_coverage["s_exif"]), int(df_coverage["s_taken_at"]),
int(df_coverage["s_camera"]), int(df_coverage["s_iso"]),
int(df_coverage["s_aperture"]), int(df_coverage["s_gps"]),
int(df_coverage["s_lens"])
]
total = int(df_coverage["celkem"])
pct = [round(v / total * 100, 1) for v in values]
fig_cov = go.Figure(go.Bar(
x=pct, y=categories, orientation='h',
text=[f"{v:,} ({p}%)" for v, p in zip(values, pct)],
textposition="auto"
))
fig_cov.update_layout(xaxis_title="% fotek", height=350)
st.plotly_chart(fig_cov, use_container_width=True)
st.divider()
st.caption("FotkyBuzalkovi — data z PostgreSQL 192.168.1.76 / fotky_buzalkovi")