Classifier work

src/beaky/image_classifier/classifier.py

@@ -1,9 +1,8 @@
 import datetime
-import logging
 import re
 from pathlib import Path
 
-from pytesseract import pytesseract
+import pytesseract
 
 from beaky.datamodels.ticket import (
     Advance,
@@ -21,27 +20,119 @@ from beaky.datamodels.ticket import (
 
 
 def img_to_text(path: str) -> str:
-    """Given a path to an image, return the text contained in that image.
+    """Read text from image using tesseract; returns empty string on error."""
-    Bypasses PIL and lets Tesseract read the file directly.
-    """
     try:
-        text = pytesseract.image_to_string(path, lang="ces")
+        return pytesseract.image_to_string(path, lang="ces").strip()
-        return text.strip()
-    except pytesseract.TesseractNotFoundError:
-        print("Error: Tesseract executable not found on your system.")
-        return ""
     except Exception as e:
         print(f"Error processing {path}: {e}")
         return ""
 
 
-def classify(text: str) -> Bet:
+def _parse_block(lines: list[str]) -> Bet:
-    """Given text extracted from an image and a date, return a Bet object that is
+    """Parses a single block of text representing exactly one bet."""
-    relevant to that text."""
+    team1, team2 = "Unknown", "Unknown"
+    league = "Unknown"
+    date_obj = datetime.datetime.now()
+    raw_text = "\n".join(lines)
 
-    logger = logging.getLogger(__name__)
+    # 1. Date extraction
+    if lines:
+        date_m = re.search(r"(\d{1,2})\.\s*(\d{1,2})\.\s*(\d{4})", lines[0])
+        if date_m:
+            try:
+                date_obj = datetime.datetime(int(date_m.group(3)), int(date_m.group(2)), int(date_m.group(1)))
+            except ValueError:
+                pass
+
+    # 2. Teams extraction (usually the line after the date)
+    if len(lines) > 1:
+        ln_norm = re.sub(r"[–—−]", "-", lines[1])
+        m = re.match(r"^(.+?)\s*-\s*(.+)$", ln_norm)
+        if m:
+            team1, team2 = m.group(1).strip(), m.group(2).strip()
+
+    # 3. League extraction (typically contains a slash and sport name)
+    for ln in lines:
+        if "/" in ln and any(sport in ln for sport in ["Fotbal", "Hokej", "Tenis"]):
+            league = ln.strip()
+            break
+
+    base_args = {"team1Name": team1, "team2Name": team2, "date": date_obj, "league": league}
+
+    # 4. Bet Type Classification (Strict parsing per tickety.md)
+    for ln in lines:
+        lower_line = ln.lower()
+
+        # Výsledek zápasu (1X2) - strict match to avoid "Výsledek 1. poločasu"
+        m_vysl = re.search(r"výsledek zápasu\s*:?\s*(1|0|x|2)$", lower_line)
+        if m_vysl and "dvojtip" not in lower_line and "remízy" not in lower_line:
+            pick = m_vysl.group(1).upper()
+            if pick == "X":
+                pick = "0"
+            return WinDrawLose(ticketType=BetType.WIN_DRAW_LOSE, betType=pick, **base_args)
+
+        # Výsledek zápasu - dvojtip (01, 02, 12, etc.)
+        m_dvoj = re.search(r"výsledek zápasu - dvojtip\s*:?\s*(10|01|02|20|12|1x|x1|x2|2x)$", lower_line)
+        if m_dvoj:
+            pick = m_dvoj.group(1).replace("x", "0").replace("X", "0")
+            # Normalize combinations to match literal definitions in ticket.py
+            if pick in ["10", "01"]:
+                pick = "01"
+            elif pick in ["20", "02"]:
+                pick = "02"
+            elif pick in ["12", "21"]:
+                pick = "12"
+
+            if pick in ["01", "12", "02"]:
+                return WinDrawLoseDouble(ticketType=BetType.WIN_DRAW_LOSE_DOUBLE, betType=pick, **base_args)
+
+        # Výsledek zápasu bez remízy (Sázka bez remízy)
+        m_bez = re.search(r"bez remízy\s*:?\s*(1|2)$", lower_line)
+        if m_bez:
+            return WinLose(ticketType=BetType.WIN_LOSE, betType=m_bez.group(1), **base_args)
+
+        # Každý z týmů dá gól v zápasu
+        m_btts = re.search(r"každý z týmů dá gól.*?:\s*(ano|ne)$", lower_line)
+        if m_btts:
+            if m_btts.group(1) == "ano":
+                return BothTeamScored(ticketType=BetType.BOTH_TEAM_SCORED, **base_args)
+            else:
+                # `ticket.py` does not currently define resolution for "Ne" logic
+                break
+
+        # Počet gólů v zápasu (e.g., Počet gólů v zápasu 2.5: + 2.5)
+        m_goals = re.search(r"počet gólů v zápasu.*?:\s*([+-])\s*([\d.]+)", lower_line)
+        if m_goals and "tým" not in lower_line:  # Avoids team-specific goals unless implemented
+            sign = m_goals.group(1)
+            val = float(m_goals.group(2))
+            is_over = sign == "+"
+            return GoalAmount(ticketType=BetType.GOAL_AMOUNT, line=val, over=is_over, **base_args)
+
+        # Kdo postoupí
+        if "postoupí" in lower_line or "postup" in lower_line:
+            return Advance(ticketType=BetType.ADVANCED, **base_args)
+
+        # Handicap v zápasu
+        m_hcp = re.search(r"handicap\s*(1|2)\s*:?\s*([+-]?[\d.]+)$", lower_line)
+        if m_hcp:
+            team_bet = m_hcp.group(1)
+            val = float(m_hcp.group(2))
+            return GoalHandicap(ticketType=BetType.GOAL_HANDICAP, team_bet=team_bet, handicap_amount=val, **base_args)
+
+    # Fallback for doubts, unknown formats (e.g., "Výsledek 1. poločasu"), or parsing failures
+    return UnknownBet(ticketType=BetType.UNKNOWN, raw_text=raw_text, **base_args)
+
+
+def classify(text: str) -> list[Bet]:
+    """Return a list of Bet objects parsed from OCR `text`.
+
+    Separates the text into chunks per bet based on date/time markers, then
+    parses each chunk individually.
+    """
+    text = (text or "").strip()
     if not text:
-        return UnknownBet(
+        return [
+            UnknownBet(
                 ticketType=BetType.UNKNOWN,
                 team1Name="N/A",
                 team2Name="N/A",
@@ -49,146 +140,75 @@ def classify(text: str) -> Bet:
                 league="N/A",
                 raw_text="No text extracted",
             )
+        ]
 
-    # 1. Defaults & Normalization
+    lines = [ln.strip() for ln in text.splitlines() if ln.strip()]
-    text_lower = text.lower()
+    bets: list[Bet] = []
-    date_obj = datetime.datetime.now()
-    team1, team2 = "Unknown", "Unknown"
-    league = "Unknown"
 
-    # 2. Heuristic extraction of Teams (Looking for "Team A - Team B" patterns)
+    # Chunk the OCR output by looking for Date/Time markers
-    lines = [line.strip() for line in text.split("\n") if line.strip()]
+    # (e.g. "pá 6. 3. 2026 21:00", "dnes 18:30")
-    for line in lines:
+    blocks = []
-        if " - " in line or " vs " in line or " v " in line:
+    current_block = []
-            # Avoid splitting on hyphens in dates or numbers
+    date_pattern = re.compile(r"(\d{1,2}\.\s*\d{1,2}\.\s*\d{4}|\bdnes\b|\bzítra\b).*?\d{2}:\d{2}", re.IGNORECASE)
-            if not re.search(r"\d\s*-\s*\d", line):
-                parts = re.split(r" - | vs | v ", line)
-                if len(parts) >= 2:
-                    team1, team2 = parts[0].strip(), parts[1].strip()
-                    break
 
-    # 3. Heuristic extraction of Date (Looking for DD.MM. YYYY HH:MM)
+    for ln in lines:
-    date_match = re.search(r"(\d{1,2}\.\s*\d{1,2}\.?\s*(?:\d{2,4})?)\s*(\d{1,2}:\d{2})?", text)
+        if date_pattern.search(ln):
-    if date_match:
+            if current_block:
-        try:
+                blocks.append(current_block)
-            # Fallback to current year if missing, basic parse attempt
+            current_block = [ln]
-            date_str = f"{date_match.group(1).replace(' ', '')} {date_match.group(2) or '00:00'}"
+        else:
-            if len(date_str.split(".")[2]) <= 5:  # Missing year
+            current_block.append(ln)
-                date_str = date_str.replace(" ", f"{datetime.datetime.now().year} ")
-            date_obj = datetime.datetime.strptime(date_str, "%d.%m.%Y %H:%M")
-        except Exception:
-            pass  # Keep default if parsing fails
 
-    # 4. Classification Logic based on keywords
+    if current_block:
-    base_args = {"team1Name": team1, "team2Name": team2, "date": date_obj, "league": league}
+        blocks.append(current_block)
 
-    # Advance / Postup
+    if not blocks:
-    if any(kw in text_lower for kw in ["postup", "postoupí", "advance"]):
+        blocks = [lines]  # Fallback if regex missed the date boundaries
-        return Advance(ticketType=BetType.ADVANCED, **base_args)
 
-    # Both Teams to Score / Oba dají gól
+    # Parse each block into a separate Bet object
-    if any(kw in text_lower for kw in ["oba dají gól", "btts", "oba týmy dají gól"]):
+    for block in blocks:
-        return BothTeamScored(ticketType=BetType.BOTH_TEAM_SCORED, **base_args)
+        bets.append(_parse_block(block))
 
-    # Goal Amount (Over/Under)
+    return bets
-    if any(kw in text_lower for kw in ["počet gólů", "více než", "méně než", "over", "under"]):
-        # Attempt to find the goal line (e.g., 2.5, 3.5)
-        line_match = re.search(r"(\d+\.\d+)", text)
-        line_val = float(line_match.group(1)) if line_match else 2.5
-        is_over = any(kw in text_lower for kw in ["více", "over", "+"])
-
-        return GoalAmount(ticketType=BetType.GOAL_AMOUNT, line=line_val, over=is_over, **base_args)
-
-    # Goal Handicap
-    if any(kw in text_lower for kw in ["handicap", "hcp"]):
-        hcp_match = re.search(r"([+-]?\d+\.\d+)", text)
-        hcp_val = float(hcp_match.group(1)) if hcp_match else 0.0
-        # Simplistic logic: guess team 1 if not explicitly stated
-        team_bet = "2" if " 2 " in text else "1"
-
-        return GoalHandicap(ticketType=BetType.GOAL_HANDICAP, team_bet=team_bet, handicap_amount=hcp_val, **base_args)
-
-    # Win Draw Lose Double (1X, X2, 12)
-    if any(kw in text_lower for kw in ["1x", "x2", "12", "dvojitá šance", "neprohra"]):
-        bet_type = "01" if "1x" in text_lower else "02" if "x2" in text_lower else "12"
-        return WinDrawLoseDouble(ticketType=BetType.WIN_DRAW_LOSE_DOUBLE, betType=bet_type, **base_args)
-
-    # Win Lose (Draw no bet / Vítěz do rozhodnutí)
-    if any(kw in text_lower for kw in ["bez remízy", "vítěz do rozhodnutí", "konečný vítěz"]):
-        bet_type = "2" if re.search(r"\b2\b", text) else "1"
-        return WinLose(ticketType=BetType.WIN_LOSE, betType=bet_type, **base_args)
-
-    # Win Draw Lose (Standard Match Odds)
-    if any(kw in text_lower for kw in ["zápas", "výsledek zápasu", "1x2"]):
-        # Look for isolated 1, X (or 0), or 2
-        match_pick = re.search(r"\b(1|x|0|2)\b", text_lower)
-        bet_type = match_pick.group(1).upper() if match_pick else "1"
-        if bet_type == "X":
-            bet_type = "0"
-
-        return WinDrawLose(ticketType=BetType.WIN_DRAW_LOSE, betType=bet_type, **base_args)
-
-    # Fallback Unknown
-    return UnknownBet(ticketType=BetType.UNKNOWN, raw_text=text, **base_args)
 
 
 def img_classify(paths: list[str], ticket_id: int) -> Ticket:
-    """Given a path to an image and a date, return a list of Tickets that are
+    """Given a list of file paths to images, classify each and collect bets into a Ticket."""
-    relevant to that image and date."""
-    # Define valid image extensions to ignore system files or text documents
     ticket = Ticket(id=ticket_id, bets=[])
     valid_extensions = {".png", ".jpg", ".jpeg", ".bmp", ".tiff", ".webp"}
 
-    # Iterate through all files in the folder
     for file in paths:
         file_path = Path(file)
-        if file_path.is_file() and file_path.suffix.lower() in valid_extensions:
+        if not (file_path.is_file() and file_path.suffix.lower() in valid_extensions):
-            # 1. Extract the text (called separately)
+            continue
+
         extracted_text = img_to_text(str(file_path))
+        print(f"--- Extracted Text from {file_path.name} ---")
         print(extracted_text)
 
-            # 2. Classify based on the extracted text (called separately)
         try:
             result = classify(extracted_text)
-            except Exception as exc:  # pragma: no cover - defensive fallback
+        except Exception as exc:
-                # Ensure result is always defined so downstream code cannot reference an unbound name
+            print(f"classify() error for {file_path}: {exc}")
-                print(f"classify() raised an exception: {exc}")
+            result = [
-                result = UnknownBet(
+                UnknownBet(
                     ticketType=BetType.UNKNOWN,
                     team1Name="N/A",
                     team2Name="N/A",
+                    date=datetime.datetime.now(),
                     league="N/A",
                     raw_text=extracted_text,
-                    date=datetime.datetime.now(),
                 )
+            ]
 
-            # 3. Add the resulting tickets to our main list
+        for bet in result:
-            # Support classifier returning either a single Bet or a list of Bet
+            print(f"-> Parsed: {bet.ticketType.value} | {bet.team1Name} vs {bet.team2Name} | {bet.league}")
-            if result is None:
-                continue
 
-            if isinstance(result, list):
-                for r in result:
-                    print(
-                        r.date,
-                        getattr(r, "ticketType", None),
-                        r.team1Name,
-                        r.team2Name,
-                        r.league,
-                    )
         ticket.bets.extend(result)
-            else:
-                print(
-                    result.date,
-                    getattr(result, "ticketType", None),
-                    result.team1Name,
-                    result.team2Name,
-                    result.league,
-                )
-                ticket.bets.append(result)
 
     return ticket
 
 
 if __name__ == "__main__":
-    img_classify(["./data/screenshots/2.png"], ticket_id=1)
+    # Test script runner
+    img_classify(["./data/screenshots/2.png"], ticket_id=2)