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