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Update Doors_Schedule.py
Browse files- Doors_Schedule.py +500 -120
Doors_Schedule.py
CHANGED
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@@ -92,9 +92,6 @@ def flexible_search(df, search_terms):
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return results
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def generate_current_table_without_cropping(clm_idx, clmn_name, df):
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selected_df = df.iloc[:, clm_idx]
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print("hello I generated the selected columns table without cropping")
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@@ -264,10 +261,131 @@ def get_selected_columns(dfs, user_patterns):
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# 3ayz akhaleehaa te search fel selected_columns column names nafsaha
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# 7ab2a 3ayz a3raf bardo maktooba ezay fel df el 7a2e2ya (akeed za ma el user medakhalha bezabt)
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def get_st_op_pattern(selected_columns, user_input):
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target = '
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if target in selected_columns.columns:
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name = user_input[2]
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return name
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@@ -455,6 +573,7 @@ def get_cleaned_width(width_info_tobeprinted):
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cleaned_width.append(clean_dimensions(w))
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return cleaned_width
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def get_widths_bb_format(cleaned_width, kelma):
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pattern = r"\bW(?:idth)?\s*[×x]\s*H(?:eight)?\b"
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match = re.search(pattern, kelma)
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@@ -566,7 +685,7 @@ def get_similar_colors_secondary(selected_columns_new, user_input):
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return dict(col_dict)
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def get_width_info_tobeprinted_secondary(new_data, main_info, secondary_info):
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width_info_tobeprinted = []
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secondary_info_tobeprinted = []
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@@ -608,6 +727,50 @@ def get_width_info_tobeprinted_secondary(new_data, main_info, secondary_info):
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h = int(float(h))
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width_info_tobeprinted.append(f"{w} mm wide x {h} mm high")
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secondary_info_tobeprinted.append((acous, fire))
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return width_info_tobeprinted, secondary_info_tobeprinted
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def get_flattened_tuples_list_SECONDARY(col_dict):
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@@ -710,6 +873,60 @@ def get_word_locations_plan_secondary(flattened_list, plan_texts, main_info, sec
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locations.append((location, lbl, w, h, clr,acoustic))
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return locations, not_found
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#SECONDARY
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def get_cleaned_data_secondary(locations, main_info, secondary_info):
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processed = defaultdict(int)
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if len(main_info) == 3 and len(secondary_info) == 1:
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for coords, label,
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if len(coords)>1:
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index = processed[label] % len(coords) # Round-robin indexing
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new_coord = [coords[index]] # Pick the correct coordinate
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@@ -797,7 +1014,7 @@ def get_cleaned_data_gpt(locations):
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return new_data
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-
def get_secondary_tobeprinted_clean(selected_secondary_info, secondary_tobeprinted, secondary_info):
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secondary_printed_clean = []
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if len(secondary_info) == 1:
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if any('Acoustic' in col for col in selected_secondary_info.columns):
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@@ -813,8 +1030,28 @@ def get_secondary_tobeprinted_clean(selected_secondary_info, secondary_tobeprint
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new_text = f"fire rating: {fire}; acoustic rating: {acous}"
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secondary_printed_clean.append(new_text)
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print(new_text)
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return secondary_printed_clean
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def mix_width_secondary(widths, secondary_printed_clean):
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all_print = []
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for i in range(len(widths)):
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@@ -829,7 +1066,7 @@ def add_bluebeam_count_annotations_secondary(pdf_bytes, locations, main_info, se
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page = pdf_document[0] # First page
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if len(main_info) == 2 and len(secondary_info) == 1:
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for loc in locations:
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coor, lbl,
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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if len(main_info) == 2 and len(secondary_info) == 2:
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for loc in locations:
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coor, lbl,
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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if len(main_info) == 3 and len(secondary_info) == 1:
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for loc in locations:
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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@@ -892,7 +1131,7 @@ def add_bluebeam_count_annotations_secondary(pdf_bytes, locations, main_info, se
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if len(main_info) == 3 and len(secondary_info) == 2:
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for loc in locations:
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coor, lbl, w,
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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if len(main_info) == 4 and len(secondary_info) == 1:
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for loc in locations:
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coor, lbl, w, h,
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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if len(main_info) == 4 and len(secondary_info) == 2:
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for loc in locations:
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coor, lbl, w, h,
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clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
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for cor in coor:
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#Create a Circle annotation (Count Markup)
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pdf_document.close()
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return output_stream.getvalue() # Return the modified PDF as bytes
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def get_user_input(user_words):
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user_input = []
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for item in user_words:
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import io
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from PyPDF2.generic import TextStringObject # ✅ Required for setting string values
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def add_bluebeam_count_annotations(pdf_bytes, locations):
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pdf_stream = io.BytesIO(pdf_bytes) # Load PDF from bytes
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pdf_document = fitz.open("pdf", pdf_stream.read()) # Open PDF in memory
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pdf_document.close()
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return output_stream.getvalue() # Return the modified PDF as bytes
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def get_user_input(user_words):
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user_input = []
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for item in user_words:
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# #Save the final modified PDF to disk
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# with open(output_pdf_path, "wb") as file:
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# file.write(final_pdf_bytes)
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def mainRun(schedule, plan, searcharray):
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if len(user_input) > 4:
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secondary_info_presence = True
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secondary_info = user_input[4:]
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if not user_input[3]:
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main_info = user_input[:3]
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elif len(user_input) > 4:
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main_info = user_input[:4]
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dfs = extract_tables(schedule)
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if secondary_info_presence:
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selected_columns_new = get_selected_columns(dfs, main_info)
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selected_secondary_info = get_secondary_info(dfs, secondary_info)
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selected_secondary_info = selected_secondary_info.applymap(lambda x: 'N/A' if isinstance(x, str) and x.strip() == '' else x)
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selected_columns_combined = pd.concat([selected_columns_new, selected_secondary_info], axis=1)
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kelma = get_st_op_pattern(selected_columns_new, user_input)
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col_dict = get_similar_colors_secondary(selected_columns_combined, user_input)
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flattened_list2 = get_flattened_tuples_list_SECONDARY(col_dict)
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for p in plan:
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plan_texts = read_text(p)
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locations, not_found = get_word_locations_plan_secondary(flattened_list2,plan_texts, main_info, secondary_info)
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new_data3 = get_cleaned_data_secondary(locations,main_info,secondary_info)
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repeated_labels = get_repeated_labels(locations)
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if kelma == None:
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#widths = get_width_info_tobeprinted_secondary(new_data3, main_info, secondary_info)
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widths, secondary_tobeprinted = get_width_info_tobeprinted_secondary(new_data3, main_info, secondary_info)
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else:
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width_info_tobeprinted, secondary_tobeprinted = get_width_info_tobeprinted_secondary(new_data3, main_info, secondary_info)
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cleaned_width = get_cleaned_width(width_info_tobeprinted)
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widths = get_widths_bb_format(cleaned_width, kelma)
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secondary_printed_clean = get_secondary_tobeprinted_clean(selected_secondary_info, secondary_tobeprinted, secondary_info)
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all_print = mix_width_secondary(widths, secondary_printed_clean)
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final_pdf_bytes = process_pdf_secondary(p, "final_output_multiple_input_new2.pdf", new_data3, all_print, main_info, secondary_info)
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pdfs.append(final_pdf_bytes)
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|
| 1221 |
plan_texts = read_text(p)
|
| 1222 |
-
|
| 1223 |
-
|
| 1224 |
-
|
| 1225 |
-
|
| 1226 |
-
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|
| 1227 |
else:
|
| 1228 |
-
|
| 1229 |
-
|
| 1230 |
-
|
| 1231 |
-
|
| 1232 |
-
|
| 1233 |
-
|
| 1234 |
-
|
| 1235 |
-
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|
| 1236 |
|
| 1237 |
-
|
| 1238 |
-
|
| 1239 |
-
|
| 1240 |
-
|
| 1241 |
-
|
| 1242 |
-
|
| 1243 |
-
|
| 1244 |
-
|
| 1245 |
-
|
| 1246 |
-
|
| 1247 |
-
|
| 1248 |
-
|
| 1249 |
-
|
| 1250 |
-
|
| 1251 |
-
|
| 1252 |
-
|
| 1253 |
-
|
| 1254 |
-
#
|
| 1255 |
-
for
|
| 1256 |
-
#
|
| 1257 |
-
|
| 1258 |
-
|
| 1259 |
-
|
| 1260 |
-
|
| 1261 |
-
|
| 1262 |
-
|
| 1263 |
-
|
| 1264 |
-
|
| 1265 |
-
|
| 1266 |
-
|
| 1267 |
-
|
| 1268 |
-
|
| 1269 |
-
|
| 1270 |
-
|
| 1271 |
-
|
|
|
|
| 92 |
return results
|
| 93 |
|
| 94 |
|
|
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|
| 95 |
def generate_current_table_without_cropping(clm_idx, clmn_name, df):
|
| 96 |
selected_df = df.iloc[:, clm_idx]
|
| 97 |
print("hello I generated the selected columns table without cropping")
|
|
|
|
| 261 |
|
| 262 |
|
| 263 |
|
| 264 |
+
def separate_main_secondary(input_user_clmn_names):
|
| 265 |
+
main_info = input_user_clmn_names[:4]
|
| 266 |
+
secondary_info = input_user_clmn_names[4:]
|
| 267 |
+
return main_info, secondary_info
|
| 268 |
+
|
| 269 |
+
|
| 270 |
+
# take main info
|
| 271 |
+
def get_column_name(user_input_m):
|
| 272 |
+
#get empty indices
|
| 273 |
+
empty_indices = [i for i, v in enumerate(user_input_m) if v == '']
|
| 274 |
+
|
| 275 |
+
# fixed column names
|
| 276 |
+
fixed_list = ["door_id", "door_type", "width", "height"]
|
| 277 |
+
for i in range(len(empty_indices)):
|
| 278 |
+
if empty_indices[i] == 3:
|
| 279 |
+
fixed_list[2] = "structural_opening"
|
| 280 |
+
fixed_list[empty_indices[i]] = ""
|
| 281 |
+
|
| 282 |
+
#finalize the column name structure
|
| 283 |
+
clmn_name_m = [i for i in fixed_list if i]
|
| 284 |
+
|
| 285 |
+
return clmn_name_m
|
| 286 |
+
|
| 287 |
+
# take secondary info
|
| 288 |
+
def get_column_name_secondary(user_input_m):
|
| 289 |
+
#get empty indices
|
| 290 |
+
empty_indices = [i for i, v in enumerate(user_input_m) if v == '']
|
| 291 |
+
|
| 292 |
+
# fixed column names
|
| 293 |
+
fixed_list = ["fire_rate", "acoustic_rate"]
|
| 294 |
+
for i in range(len(empty_indices)):
|
| 295 |
+
fixed_list[empty_indices[i]] = ""
|
| 296 |
+
|
| 297 |
+
#finalize the column name structure
|
| 298 |
+
clmn_name_m = [i for i in fixed_list if i]
|
| 299 |
+
|
| 300 |
+
return clmn_name_m
|
| 301 |
+
|
| 302 |
+
|
| 303 |
+
#handling both main and secondary info together in one table
|
| 304 |
+
def get_selected_columns_all(dfs, user_patterns):
|
| 305 |
+
selected_columns = []
|
| 306 |
+
selected_columns_new = None # Initialize selected_columns_new to None
|
| 307 |
+
|
| 308 |
+
for i in range(len(dfs)):
|
| 309 |
+
|
| 310 |
+
|
| 311 |
+
|
| 312 |
+
|
| 313 |
+
|
| 314 |
+
main_info, secondary_info = separate_main_secondary(user_patterns)
|
| 315 |
+
clmn_name_main = get_column_name(main_info)
|
| 316 |
+
non_empty_main_info = [item for item in main_info if item]
|
| 317 |
+
|
| 318 |
+
clmn_name_secondary = get_column_name_secondary(secondary_info)
|
| 319 |
+
|
| 320 |
+
|
| 321 |
+
non_empty_secondary_info = [item for item in secondary_info if item]
|
| 322 |
+
|
| 323 |
+
clmn_name = clmn_name_main + clmn_name_secondary
|
| 324 |
+
non_empty_info = non_empty_main_info + non_empty_secondary_info
|
| 325 |
+
|
| 326 |
+
#print(f"main info: {main_info}")
|
| 327 |
+
print(f"clmn name: {clmn_name}")
|
| 328 |
+
print(f"non-empty info: {non_empty_info}")
|
| 329 |
+
#print(f"length of non-empty info: {len(non_empty_main_info)}")
|
| 330 |
+
|
| 331 |
+
|
| 332 |
+
cell_columns_appearance = flexible_search(dfs[i], non_empty_info)
|
| 333 |
+
cell_matches, col_matches = analyse_cell_columns(cell_columns_appearance)
|
| 334 |
+
|
| 335 |
+
print(f"length of cell_matches: {len(cell_matches)}")
|
| 336 |
+
print(f"cell_matches: {cell_matches}")
|
| 337 |
+
#clmn_name = map_user_input_to_standard_labels(user_patterns)
|
| 338 |
+
#if len(clmn_name) < len(user_patterns):
|
| 339 |
+
|
| 340 |
+
|
| 341 |
+
|
| 342 |
+
|
| 343 |
+
print(clmn_name)
|
| 344 |
+
|
| 345 |
+
if len(cell_matches) == 0 and len(col_matches) == 0:
|
| 346 |
+
print(f"this is df {i}, SEARCH IN ANOTHER DF")
|
| 347 |
+
|
| 348 |
+
else:
|
| 349 |
+
#IN COLUMNS
|
| 350 |
+
if len(col_matches) == len(non_empty_info):
|
| 351 |
+
column_index_list = get_column_index(col_matches)
|
| 352 |
+
print(f"this is df {i} mawgooda fel columns, check el df length 3ashan law el details fe table tany")
|
| 353 |
+
#print(len(clm_idx))
|
| 354 |
+
#details in another table
|
| 355 |
+
print(column_index_list)
|
| 356 |
+
if len(dfs[i]) <10:
|
| 357 |
+
selected_columns_new = details_in_another_table(clmn_name, column_index_list, dfs[i], dfs)
|
| 358 |
+
#break
|
| 359 |
+
#other_matches = details_in_another_table_mod(clmn_name, clmn_idx, dfs[i], dfs)
|
| 360 |
+
#details in the same table
|
| 361 |
+
if len(dfs[i]) >10:
|
| 362 |
+
selected_columns_new = generate_current_table_without_cropping(column_index_list,dfs[i])
|
| 363 |
+
#break
|
| 364 |
+
|
| 365 |
+
#IN CELLS
|
| 366 |
+
if len(cell_matches) == len(non_empty_info):
|
| 367 |
+
row_index_list, column_index_list = get_row_column_indices(cell_matches)
|
| 368 |
+
print(f"this is df {i} mawgooda fel cells, check el df length 3ashan law el details fe table tany")
|
| 369 |
+
|
| 370 |
+
#details in another table
|
| 371 |
+
#if len(dfs[i]) <2:
|
| 372 |
+
#selected_columns_new = details_in_another_table(clmn_name, clmn_idx, dfs[i], dfs)
|
| 373 |
+
selected_columns_new = details_in_another_table(clmn_name, column_index_list, dfs[i], dfs)
|
| 374 |
+
selected_columns_new = crop_rename_table(row_index_list, clmn_name, column_index_list,dfs[i])
|
| 375 |
+
|
| 376 |
+
break
|
| 377 |
+
#other_matches = details_in_another_table_mod(clmn_name, clmn_idx, dfs[i], dfs)
|
| 378 |
+
##details in the same table
|
| 379 |
+
#if len(dfs[i]) >2:
|
| 380 |
+
# #print(f"this is df {i} call crop_rename_table(indices, clmn_name, clmn_idx,df)")
|
| 381 |
+
#break
|
| 382 |
+
return selected_columns_new
|
| 383 |
+
|
| 384 |
+
|
| 385 |
# 3ayz akhaleehaa te search fel selected_columns column names nafsaha
|
| 386 |
# 7ab2a 3ayz a3raf bardo maktooba ezay fel df el 7a2e2ya (akeed za ma el user medakhalha bezabt)
|
| 387 |
def get_st_op_pattern(selected_columns, user_input):
|
| 388 |
+
target = 'structural_opening'
|
| 389 |
if target in selected_columns.columns:
|
| 390 |
name = user_input[2]
|
| 391 |
return name
|
|
|
|
| 573 |
cleaned_width.append(clean_dimensions(w))
|
| 574 |
return cleaned_width
|
| 575 |
|
| 576 |
+
|
| 577 |
def get_widths_bb_format(cleaned_width, kelma):
|
| 578 |
pattern = r"\bW(?:idth)?\s*[×x]\s*H(?:eight)?\b"
|
| 579 |
match = re.search(pattern, kelma)
|
|
|
|
| 685 |
|
| 686 |
return dict(col_dict)
|
| 687 |
|
| 688 |
+
'''def get_width_info_tobeprinted_secondary(new_data, main_info, secondary_info):
|
| 689 |
width_info_tobeprinted = []
|
| 690 |
secondary_info_tobeprinted = []
|
| 691 |
|
|
|
|
| 727 |
h = int(float(h))
|
| 728 |
width_info_tobeprinted.append(f"{w} mm wide x {h} mm high")
|
| 729 |
secondary_info_tobeprinted.append((acous, fire))
|
| 730 |
+
return width_info_tobeprinted, secondary_info_tobeprinted'''
|
| 731 |
+
|
| 732 |
+
def get_width_info_tobeprinted_secondary(new_data, main_info, secondary_info):
|
| 733 |
+
width_info_tobeprinted = []
|
| 734 |
+
secondary_info_tobeprinted = []
|
| 735 |
+
|
| 736 |
+
if len(main_info) == 2 and len(secondary_info) == 1:
|
| 737 |
+
for coords, label, acous, color in new_data:
|
| 738 |
+
secondary_info_tobeprinted.append(acous)
|
| 739 |
+
|
| 740 |
+
|
| 741 |
+
if len(main_info) == 2 and len(secondary_info) == 2:
|
| 742 |
+
for coords, label, acous, fire, color in new_data:
|
| 743 |
+
secondary_info_tobeprinted.append((acous, fire))
|
| 744 |
+
|
| 745 |
+
if len(main_info) == 3 and len(secondary_info) == 1:
|
| 746 |
+
for coords, label, width, acous, color in new_data:
|
| 747 |
+
width_info_tobeprinted.append(width)
|
| 748 |
+
secondary_info_tobeprinted.append(acous)
|
| 749 |
+
|
| 750 |
+
|
| 751 |
+
if len(main_info) == 3 and len(secondary_info) == 2:
|
| 752 |
+
for coords, label, width, acous, fire, color in new_data:
|
| 753 |
+
width_info_tobeprinted.append(width)
|
| 754 |
+
secondary_info_tobeprinted.append((acous, fire))
|
| 755 |
+
|
| 756 |
+
if len(main_info) == 4 and len(secondary_info) == 1:
|
| 757 |
+
for coords, label, width, height, acous, color in new_data:
|
| 758 |
+
w = re.sub(r",", "", width)
|
| 759 |
+
h = re.sub(r",", "", height)
|
| 760 |
+
w = int(float(w))
|
| 761 |
+
h = int(float(h))
|
| 762 |
+
width_info_tobeprinted.append(f"{w} mm wide x {h} mm high")
|
| 763 |
+
secondary_info_tobeprinted.append(acous)
|
| 764 |
+
|
| 765 |
+
|
| 766 |
+
if len(main_info) == 4 and len(secondary_info) == 2:
|
| 767 |
+
for coords, label, width, height, acous, fire, color in new_data:
|
| 768 |
+
w = re.sub(r",", "", width)
|
| 769 |
+
h = re.sub(r",", "", height)
|
| 770 |
+
w = int(float(w))
|
| 771 |
+
h = int(float(h))
|
| 772 |
+
width_info_tobeprinted.append(f"{w} mm wide x {h} mm high")
|
| 773 |
+
secondary_info_tobeprinted.append((acous, fire))
|
| 774 |
return width_info_tobeprinted, secondary_info_tobeprinted
|
| 775 |
|
| 776 |
def get_flattened_tuples_list_SECONDARY(col_dict):
|
|
|
|
| 873 |
locations.append((location, lbl, w, h, clr,acoustic))
|
| 874 |
return locations, not_found
|
| 875 |
|
| 876 |
+
### newest, accept combined table
|
| 877 |
+
from collections import defaultdict
|
| 878 |
+
import random
|
| 879 |
+
|
| 880 |
+
def get_similar_colors_all(selected_columns_new):
|
| 881 |
+
def generate_rgb():
|
| 882 |
+
return (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
|
| 883 |
+
|
| 884 |
+
unique_keys = selected_columns_new['door_type'].unique()
|
| 885 |
+
key_colors = {key: generate_rgb() for key in unique_keys}
|
| 886 |
+
|
| 887 |
+
#Column fields
|
| 888 |
+
clmns_fields = selected_columns_new.columns.to_list()
|
| 889 |
+
|
| 890 |
+
def col_template():
|
| 891 |
+
d = {
|
| 892 |
+
'values': [],
|
| 893 |
+
'color': None
|
| 894 |
+
}
|
| 895 |
+
for field in clmns_fields:
|
| 896 |
+
d[field] = []
|
| 897 |
+
return d
|
| 898 |
+
|
| 899 |
+
col_dict = defaultdict(col_template)
|
| 900 |
+
|
| 901 |
+
for _, row in selected_columns_new.iterrows():
|
| 902 |
+
key = row['door_type']
|
| 903 |
+
col_dict[key]['values'].append(row['door_id'])
|
| 904 |
+
|
| 905 |
+
for field in clmns_fields:
|
| 906 |
+
col_dict[key][field].append(row.get(field, None))
|
| 907 |
+
|
| 908 |
+
col_dict[key]['color'] = key_colors[key]
|
| 909 |
+
|
| 910 |
+
return dict(col_dict)
|
| 911 |
+
|
| 912 |
+
### newest, accept combined table
|
| 913 |
+
def get_flattened_tuples_list_all(col_dict):
|
| 914 |
+
exclude_fields = ['door_type', 'values']
|
| 915 |
+
flattened_list = []
|
| 916 |
+
|
| 917 |
+
for values_dict in col_dict.values():
|
| 918 |
+
# All fields that are lists and not in the excluded fields
|
| 919 |
+
list_fields = [k for k, v in values_dict.items()
|
| 920 |
+
if isinstance(v, list) and k not in exclude_fields]
|
| 921 |
+
n_rows = len(values_dict[list_fields[0]]) if list_fields else 0
|
| 922 |
+
|
| 923 |
+
for i in range(n_rows):
|
| 924 |
+
tuple_row = tuple(values_dict[field][i] for field in list_fields) + (values_dict['color'],)
|
| 925 |
+
flattened_list.append(tuple_row)
|
| 926 |
+
|
| 927 |
+
return flattened_list
|
| 928 |
+
|
| 929 |
+
|
| 930 |
#SECONDARY
|
| 931 |
def get_cleaned_data_secondary(locations, main_info, secondary_info):
|
| 932 |
processed = defaultdict(int)
|
|
|
|
| 954 |
|
| 955 |
|
| 956 |
if len(main_info) == 3 and len(secondary_info) == 1:
|
| 957 |
+
for coords, label, width, color, acous in locations:
|
| 958 |
if len(coords)>1:
|
| 959 |
index = processed[label] % len(coords) # Round-robin indexing
|
| 960 |
new_coord = [coords[index]] # Pick the correct coordinate
|
|
|
|
| 1014 |
|
| 1015 |
return new_data
|
| 1016 |
|
| 1017 |
+
'''def get_secondary_tobeprinted_clean(selected_secondary_info, secondary_tobeprinted, secondary_info):
|
| 1018 |
secondary_printed_clean = []
|
| 1019 |
if len(secondary_info) == 1:
|
| 1020 |
if any('Acoustic' in col for col in selected_secondary_info.columns):
|
|
|
|
| 1030 |
new_text = f"fire rating: {fire}; acoustic rating: {acous}"
|
| 1031 |
secondary_printed_clean.append(new_text)
|
| 1032 |
print(new_text)
|
| 1033 |
+
return secondary_printed_clean'''
|
| 1034 |
+
|
| 1035 |
+
|
| 1036 |
+
def get_secondary_tobeprinted_clean(selected_secondary_info, secondary_tobeprinted, secondary_info):
|
| 1037 |
+
secondary_printed_clean = []
|
| 1038 |
+
if len(secondary_info) == 1:
|
| 1039 |
+
if any('acoustic' in col for col in selected_secondary_info.columns):
|
| 1040 |
+
for acous in secondary_tobeprinted:
|
| 1041 |
+
new_text = f"acoustic rating: {acous};"
|
| 1042 |
+
secondary_printed_clean.append(new_text)
|
| 1043 |
+
if any('fire' in col for col in selected_secondary_info.columns):
|
| 1044 |
+
for fire in secondary_tobeprinted:
|
| 1045 |
+
new_text = f"fire rating: {fire};"
|
| 1046 |
+
secondary_printed_clean.append(new_text)
|
| 1047 |
+
if len(secondary_info) == 2:
|
| 1048 |
+
for fire, acous in secondary_tobeprinted:
|
| 1049 |
+
new_text = f"fire rating: {fire}; acoustic rating: {acous};"
|
| 1050 |
+
secondary_printed_clean.append(new_text)
|
| 1051 |
+
print(new_text)
|
| 1052 |
return secondary_printed_clean
|
| 1053 |
|
| 1054 |
+
|
| 1055 |
def mix_width_secondary(widths, secondary_printed_clean):
|
| 1056 |
all_print = []
|
| 1057 |
for i in range(len(widths)):
|
|
|
|
| 1066 |
page = pdf_document[0] # First page
|
| 1067 |
if len(main_info) == 2 and len(secondary_info) == 1:
|
| 1068 |
for loc in locations:
|
| 1069 |
+
coor, lbl, acous, clr = loc
|
| 1070 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1071 |
for cor in coor:
|
| 1072 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1087 |
|
| 1088 |
if len(main_info) == 2 and len(secondary_info) == 2:
|
| 1089 |
for loc in locations:
|
| 1090 |
+
coor, lbl, acous, fire, clr = loc
|
| 1091 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1092 |
for cor in coor:
|
| 1093 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1108 |
|
| 1109 |
if len(main_info) == 3 and len(secondary_info) == 1:
|
| 1110 |
for loc in locations:
|
| 1111 |
+
if len(loc) != 5:
|
| 1112 |
+
continue
|
| 1113 |
+
coor, lbl, w, acous, clr = loc
|
| 1114 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1115 |
for cor in coor:
|
| 1116 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1131 |
|
| 1132 |
if len(main_info) == 3 and len(secondary_info) == 2:
|
| 1133 |
for loc in locations:
|
| 1134 |
+
coor, lbl, w, acous, fire, clr = loc
|
| 1135 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1136 |
for cor in coor:
|
| 1137 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1152 |
|
| 1153 |
if len(main_info) == 4 and len(secondary_info) == 1:
|
| 1154 |
for loc in locations:
|
| 1155 |
+
coor, lbl, w, h, acous, clr = loc
|
| 1156 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1157 |
for cor in coor:
|
| 1158 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1173 |
|
| 1174 |
if len(main_info) == 4 and len(secondary_info) == 2:
|
| 1175 |
for loc in locations:
|
| 1176 |
+
coor, lbl, w, h, acous, fire, clr = loc
|
| 1177 |
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1178 |
for cor in coor:
|
| 1179 |
#Create a Circle annotation (Count Markup)
|
|
|
|
| 1200 |
pdf_document.close()
|
| 1201 |
|
| 1202 |
return output_stream.getvalue() # Return the modified PDF as bytes
|
| 1203 |
+
|
| 1204 |
def get_user_input(user_words):
|
| 1205 |
user_input = []
|
| 1206 |
for item in user_words:
|
|
|
|
| 1255 |
import io
|
| 1256 |
from PyPDF2.generic import TextStringObject # ✅ Required for setting string values
|
| 1257 |
|
| 1258 |
+
'''def add_bluebeam_count_annotations(pdf_bytes, locations):
|
| 1259 |
pdf_stream = io.BytesIO(pdf_bytes) # Load PDF from bytes
|
| 1260 |
pdf_document = fitz.open("pdf", pdf_stream.read()) # Open PDF in memory
|
| 1261 |
|
|
|
|
| 1327 |
pdf_document.close()
|
| 1328 |
|
| 1329 |
return output_stream.getvalue() # Return the modified PDF as bytes
|
| 1330 |
+
'''
|
| 1331 |
+
def add_bluebeam_count_annotations(pdf_bytes, locations):
|
| 1332 |
+
pdf_stream = io.BytesIO(pdf_bytes) # Load PDF from bytes
|
| 1333 |
+
pdf_document = fitz.open("pdf", pdf_stream.read()) # Open PDF in memory
|
| 1334 |
+
|
| 1335 |
+
page = pdf_document[0] # First page
|
| 1336 |
+
print(f"length of locations 0 from not sec presence: {len(locations[0])}")
|
| 1337 |
+
|
| 1338 |
+
for loc in locations:
|
| 1339 |
+
|
| 1340 |
+
if len(loc) == 3:
|
| 1341 |
+
coor, lbl, clr = loc
|
| 1342 |
+
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1343 |
+
for cor in coor:
|
| 1344 |
+
#Create a Circle annotation (Count Markup)
|
| 1345 |
+
annot = page.add_circle_annot(
|
| 1346 |
+
fitz.Rect(cor[0] - 10, cor[1] - 10, cor[0] + 10, cor[1] + 10) # Small circle
|
| 1347 |
+
)
|
| 1348 |
+
|
| 1349 |
+
#Assign required Bluebeam metadata
|
| 1350 |
+
annot.set_colors(stroke=clr, fill=(1, 1, 1)) # Set stroke color and fill white
|
| 1351 |
+
annot.set_border(width=2) # Border thickness
|
| 1352 |
+
annot.set_opacity(1) # Fully visible
|
| 1353 |
+
|
| 1354 |
+
#Set annotation properties for Bluebeam Count detection
|
| 1355 |
+
annot.set_info("name", lbl) # Unique name for each count
|
| 1356 |
+
annot.set_info("subject", "Count") #Bluebeam uses "Count" for Count markups
|
| 1357 |
+
annot.set_info("title", lbl) # Optional
|
| 1358 |
+
annot.update() # Apply changes
|
| 1359 |
+
if len(loc) == 4:
|
| 1360 |
+
coor, lbl, clr,w = loc
|
| 1361 |
+
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1362 |
+
for cor in coor:
|
| 1363 |
+
#Create a Circle annotation (Count Markup)
|
| 1364 |
+
annot = page.add_circle_annot(
|
| 1365 |
+
fitz.Rect(cor[0] - 10, cor[1] - 10, cor[0] + 10, cor[1] + 10) # Small circle
|
| 1366 |
+
)
|
| 1367 |
+
|
| 1368 |
+
#Assign required Bluebeam metadata
|
| 1369 |
+
annot.set_colors(stroke=clr, fill=(1, 1, 1)) # Set stroke color and fill white
|
| 1370 |
+
annot.set_border(width=2) # Border thickness
|
| 1371 |
+
annot.set_opacity(1) # Fully visible
|
| 1372 |
+
|
| 1373 |
+
#Set annotation properties for Bluebeam Count detection
|
| 1374 |
+
annot.set_info("name", lbl) # Unique name for each count
|
| 1375 |
+
annot.set_info("subject", "Count") #Bluebeam uses "Count" for Count markups
|
| 1376 |
+
annot.set_info("title", lbl) # Optional
|
| 1377 |
+
annot.update() # Apply changes
|
| 1378 |
+
|
| 1379 |
+
if len(loc) == 5:
|
| 1380 |
+
coor, lbl, clr,w,h = loc
|
| 1381 |
+
clr = (clr[0] / 255, clr[1] / 255, clr[2] / 255)
|
| 1382 |
+
for cor in coor:
|
| 1383 |
+
#Create a Circle annotation (Count Markup)
|
| 1384 |
+
annot = page.add_circle_annot(
|
| 1385 |
+
fitz.Rect(cor[0] - 10, cor[1] - 10, cor[0] + 10, cor[1] + 10) # Small circle
|
| 1386 |
+
)
|
| 1387 |
+
|
| 1388 |
+
#Assign required Bluebeam metadata
|
| 1389 |
+
annot.set_colors(stroke=clr, fill=(1, 1, 1)) # Set stroke color and fill white
|
| 1390 |
+
annot.set_border(width=2) # Border thickness
|
| 1391 |
+
annot.set_opacity(1) # Fully visible
|
| 1392 |
+
|
| 1393 |
+
#Set annotation properties for Bluebeam Count detection
|
| 1394 |
+
annot.set_info("name", lbl) # Unique name for each count
|
| 1395 |
+
annot.set_info("subject", "Count") #Bluebeam uses "Count" for Count markups
|
| 1396 |
+
annot.set_info("title", lbl) # Optional
|
| 1397 |
+
annot.update() # Apply changes
|
| 1398 |
+
|
| 1399 |
+
#Save modified PDF to a variable instead of a file
|
| 1400 |
+
output_stream = io.BytesIO()
|
| 1401 |
+
pdf_document.save(output_stream)
|
| 1402 |
+
pdf_document.close()
|
| 1403 |
+
|
| 1404 |
+
return output_stream.getvalue() # Return the modified PDF as bytes
|
| 1405 |
+
|
| 1406 |
+
|
| 1407 |
def get_user_input(user_words):
|
| 1408 |
user_input = []
|
| 1409 |
for item in user_words:
|
|
|
|
| 1474 |
# #Save the final modified PDF to disk
|
| 1475 |
# with open(output_pdf_path, "wb") as file:
|
| 1476 |
# file.write(final_pdf_bytes)
|
| 1477 |
+
|
| 1478 |
+
def process_pdf_secondary(input_pdf_path, output_pdf_path, locations, new_authors, main_info, secondary_info):
|
| 1479 |
+
|
| 1480 |
+
if isinstance(input_pdf_path, bytes):
|
| 1481 |
+
original_pdf_bytes = input_pdf_path
|
| 1482 |
+
else:
|
| 1483 |
+
with open(input_pdf_path, "rb") as file:
|
| 1484 |
+
original_pdf_bytes = file.read()
|
| 1485 |
+
|
| 1486 |
+
#Add Bluebeam-compatible count annotations
|
| 1487 |
+
annotated_pdf_bytes = add_bluebeam_count_annotations_secondary(original_pdf_bytes, locations, main_info, secondary_info)
|
| 1488 |
+
|
| 1489 |
+
#Modify author field using PyPDF2
|
| 1490 |
+
final_pdf_bytes = modify_author_in_pypdf2(annotated_pdf_bytes, new_authors)
|
| 1491 |
+
|
| 1492 |
+
return final_pdf_bytes
|
| 1493 |
+
|
| 1494 |
+
|
| 1495 |
+
def process_pdf(input_pdf_path, output_pdf_path, locations, new_authors):
|
| 1496 |
+
#Load original PDF
|
| 1497 |
+
if isinstance(input_pdf_path, bytes):
|
| 1498 |
+
original_pdf_bytes = input_pdf_path
|
| 1499 |
+
else:
|
| 1500 |
+
with open(input_pdf_path, "rb") as file:
|
| 1501 |
+
original_pdf_bytes = file.read()
|
| 1502 |
+
|
| 1503 |
+
#Add Bluebeam-compatible count annotations
|
| 1504 |
+
annotated_pdf_bytes = add_bluebeam_count_annotations(original_pdf_bytes, locations)
|
| 1505 |
+
|
| 1506 |
+
#Modify author field using PyPDF2
|
| 1507 |
+
final_pdf_bytes = modify_author_in_pypdf2(annotated_pdf_bytes, new_authors)
|
| 1508 |
+
return final_pdf_bytes
|
| 1509 |
def mainRun(schedule, plan, searcharray):
|
| 1510 |
+
|
| 1511 |
+
#print(type(plan))
|
| 1512 |
+
eltype = type(plan)
|
| 1513 |
+
print(f"el type beta3 variable plan:: {eltype}")
|
| 1514 |
+
len_plan = len(plan)
|
| 1515 |
+
print(f"length of the plan's array is: {len_plan}")
|
| 1516 |
+
p1_type = type(plan[0])
|
| 1517 |
+
print(f"el mawgood fe p[0]: {p1_type}")
|
| 1518 |
+
|
| 1519 |
+
print(f"search array: {searcharray}")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1520 |
|
| 1521 |
+
dfs = extract_tables(schedule)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1522 |
|
| 1523 |
+
pdfs = []
|
| 1524 |
+
for p in plan:
|
| 1525 |
+
all_new_data = []
|
| 1526 |
+
all_widths = []
|
| 1527 |
+
pdf_outputs = []
|
| 1528 |
+
|
| 1529 |
+
for j in range(len(searcharray)):
|
| 1530 |
+
user_input = searcharray[j]
|
| 1531 |
+
|
| 1532 |
+
secondary_presence = False
|
| 1533 |
+
if user_input[4] or user_input[5]:
|
| 1534 |
+
secondary_presence = True
|
| 1535 |
+
main_info_, secondary_info_ = separate_main_secondary(user_input)
|
| 1536 |
+
main_info = [item for item in main_info_ if item]
|
| 1537 |
+
secondary_info = [item for item in secondary_info_ if item]
|
| 1538 |
+
print("feh secondary information")
|
| 1539 |
+
if user_input[4]:
|
| 1540 |
+
print("Fire rate mawgooda")
|
| 1541 |
+
if user_input[5]:
|
| 1542 |
+
print("Acoustic Rate mawgooda")
|
| 1543 |
+
else:
|
| 1544 |
+
print("mafeesh secondary information")
|
| 1545 |
+
|
| 1546 |
+
selected_columns_combined = get_selected_columns_all(dfs, user_input)
|
| 1547 |
+
kelma = get_st_op_pattern(selected_columns_combined, user_input)
|
| 1548 |
+
col_dict = get_similar_colors_all(selected_columns_combined)
|
| 1549 |
+
flattened_list = get_flattened_tuples_list_all(col_dict)
|
| 1550 |
plan_texts = read_text(p)
|
| 1551 |
+
|
| 1552 |
+
if secondary_presence:
|
| 1553 |
+
plan_texts = read_text(p)
|
| 1554 |
+
locations, not_found = get_word_locations_plan_secondary(flattened_list,plan_texts, main_info, secondary_info)
|
| 1555 |
+
new_data3 = get_cleaned_data_secondary(locations,main_info,secondary_info)
|
| 1556 |
+
|
| 1557 |
+
#Single page annotation
|
| 1558 |
+
all_new_data.append(new_data3)
|
| 1559 |
+
repeated_labels = get_repeated_labels(locations)
|
| 1560 |
+
if kelma == None:
|
| 1561 |
+
widths, secondary_tobeprinted = get_width_info_tobeprinted_secondary(new_data3, main_info, secondary_info)
|
| 1562 |
+
else:
|
| 1563 |
+
width_info_tobeprinted, secondary_tobeprinted = get_width_info_tobeprinted_secondary(new_data3, main_info, secondary_info)
|
| 1564 |
+
cleaned_width = get_cleaned_width(width_info_tobeprinted)
|
| 1565 |
+
widths = get_widths_bb_format(cleaned_width, kelma)
|
| 1566 |
+
#Handling schedules without dimensions (width and height)
|
| 1567 |
+
if selected_columns_combined.shape[1] == 2:
|
| 1568 |
+
widths = []
|
| 1569 |
+
|
| 1570 |
+
secondary_printed_clean = get_secondary_tobeprinted_clean(selected_columns_combined, secondary_tobeprinted, secondary_info)
|
| 1571 |
+
all_print = mix_width_secondary(widths, secondary_printed_clean)
|
| 1572 |
+
|
| 1573 |
+
#Single page annotation
|
| 1574 |
+
all_widths.append(all_print)
|
| 1575 |
+
|
| 1576 |
+
#flat_list_new_data = [item for sublist in all_new_data for item in sublist]
|
| 1577 |
+
#flat_list_widths = [item for sublist in all_widths for item in sublist]
|
| 1578 |
+
|
| 1579 |
+
if pdf_outputs:
|
| 1580 |
+
final_pdf_bytes = process_pdf_secondary(pdf_outputs[j-1], "final_output_multiple_input_new2.pdf", all_new_data[j], all_widths[j], main_info, secondary_info)
|
| 1581 |
+
pdf_outputs.append(final_pdf_bytes)
|
| 1582 |
+
else:
|
| 1583 |
+
final_pdf_bytes = process_pdf_secondary(p, "final_output_multiple_input_new2.pdf", all_new_data[j], all_widths[j], main_info, secondary_info)
|
| 1584 |
+
pdf_outputs.append(final_pdf_bytes)
|
| 1585 |
+
|
| 1586 |
else:
|
| 1587 |
+
locations, not_found = get_word_locations_plan(flattened_list,plan_texts)
|
| 1588 |
+
new_data = get_cleaned_data(locations)
|
| 1589 |
+
#Single page annotation
|
| 1590 |
+
all_new_data.append(new_data)
|
| 1591 |
+
repeated_labels = get_repeated_labels(locations)
|
| 1592 |
+
if kelma == None:
|
| 1593 |
+
widths = get_width_info_tobeprinted(new_data)
|
| 1594 |
+
else:
|
| 1595 |
+
width_info_tobeprinted = get_width_info_tobeprinted(new_data)
|
| 1596 |
+
cleaned_width = get_cleaned_width(width_info_tobeprinted)
|
| 1597 |
+
widths = get_widths_bb_format(cleaned_width, kelma)
|
| 1598 |
+
|
| 1599 |
+
#Handling schedules without dimensions (width and height)
|
| 1600 |
+
if selected_columns_combined.shape[1] == 2:
|
| 1601 |
+
widths = []
|
| 1602 |
+
|
| 1603 |
+
#Single page annotation
|
| 1604 |
+
all_widths.append(widths)
|
| 1605 |
+
|
| 1606 |
+
flat_list_new_data = [item for sublist in all_new_data for item in sublist]
|
| 1607 |
+
flat_list_widths = [item for sublist in all_widths for item in sublist]
|
| 1608 |
+
|
| 1609 |
+
if pdf_outputs:
|
| 1610 |
+
final_pdf_bytes = process_pdf(pdf_outputs[j-1], "final_output_width_trial.pdf", all_new_data[j], all_widths[j])
|
| 1611 |
+
pdf_outputs.append(final_pdf_bytes)
|
| 1612 |
+
else:
|
| 1613 |
+
final_pdf_bytes = process_pdf(p, "final_output_width_trial.pdf", all_new_data[j], all_widths[j])
|
| 1614 |
+
pdf_outputs.append(final_pdf_bytes)
|
| 1615 |
+
|
| 1616 |
|
| 1617 |
+
pdfs.append(final_pdf_bytes)
|
| 1618 |
+
merged_pdf = merge_pdf_bytes_list(pdfs)
|
| 1619 |
+
print(f"number of pges of merged_pdf is {len(merged_pdf)} and its type is {type(merged_pdf)}")
|
| 1620 |
+
|
| 1621 |
+
not_found = []
|
| 1622 |
+
doc2 =fitz.open('pdf',merged_pdf)
|
| 1623 |
+
len_doc2 = len(doc2)
|
| 1624 |
+
print(f"number of pges of doc2 is {len_doc2} and its type is {type(doc2)}")
|
| 1625 |
+
page=doc2[0]
|
| 1626 |
+
pix = page.get_pixmap() # render page to an image
|
| 1627 |
+
pl=Image.frombytes('RGB', [pix.width,pix.height],pix.samples)
|
| 1628 |
+
img=np.array(pl)
|
| 1629 |
+
annotatedimg = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
|
| 1630 |
+
|
| 1631 |
+
|
| 1632 |
+
list1=pd.DataFrame(columns=['content', 'id', 'subject','color'])
|
| 1633 |
+
|
| 1634 |
+
# for page in doc:
|
| 1635 |
+
for page in doc2:
|
| 1636 |
+
# Iterate through annotations on the page
|
| 1637 |
+
for annot in page.annots():
|
| 1638 |
+
# Get the color of the annotation
|
| 1639 |
+
annot_color = annot.colors
|
| 1640 |
+
if annot_color is not None:
|
| 1641 |
+
# annot_color is a dictionary with 'stroke' and 'fill' keys
|
| 1642 |
+
stroke_color = annot_color.get('stroke') # Border color
|
| 1643 |
+
fill_color = annot_color.get('fill') # Fill color
|
| 1644 |
+
if fill_color:
|
| 1645 |
+
v='fill'
|
| 1646 |
+
# print('fill')
|
| 1647 |
+
if stroke_color:
|
| 1648 |
+
v='stroke'
|
| 1649 |
+
x,y,z=int(annot_color.get(v)[0]*255),int(annot_color.get(v)[1]*255),int(annot_color.get(v)[2]*255)
|
| 1650 |
+
list1.loc[len(list1)] =[annot.info['content'],annot.info['id'],annot.info['subject'],[x,y,z]]
|
| 1651 |
+
return annotatedimg, doc2 , list1, repeated_labels , not_found
|